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School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 3 c c From the textbook solve the problems 29, 30, 31, 32 and 33 from the Chapter 4. Solve the problems 1, 2, 4, 5 and 6 from the Chapter 4 additional exercises at http:/www.athenasc.com
School: UCLA
Sule Ozler Economics 12 Fall 2011 READ THE EXPLANATIONS IN BOLD LETTERS CAREFULLY! MID-TERM EXAM - GOOD LUCK! WRITE YOUR NAME AND ID# You will not be allowed to ask questions during the exam. This exam has three sections. Each section has multiple questio
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi c c Homework 1 From the textbook solve the problems 1, 2, 3, 5, 6, 8, 11 and 14 at the end of the Chapter 4. And also the problems below: Problem 1. Give examples of (not independent) random variab
School: UCLA
Spring 2011- Professor Sule Ozler Name Economics 121 ID# MID-TERM EXAM-II WRITE YOUR NAME AND ID# This exam has TWO sections. Each section has multiple questions. Sections I is 40 points, section II is for a total of 60 points. I. MULTIPLE CHOICE: Choose
School: UCLA
Course: Mathemtcl Modeling
Math 142-2, Homework 1 Solutions April 7, 2014 Problem 34.4 Suppose the growth rate of a certain species is not constant, but depends in a known way on the temperature of its environment. If the temperature is known as a function of time, derive an expres
School: UCLA
Spring 2011- Professor Sule Ozler Name Economics 121 ID# FINAL EXAM WRITE YOUR NAME AND ID# No questions will be answered during the exam There will not be any bathroom breaks during the exam You are permitted to have only your writing equipment on your d
School: UCLA
Chapter Review Exercises SOLUTION 811 The function whose value we want to approximate is f (x, y, z) = x 2 + y2 + z We use the linear approximation at the point (7, 5, 70), hence h = 7.1 - 7 = 0.1, k = 4.9 - 5 = -0.1, and l = 70.1 - 70 = 0.1. We g
School: UCLA
MULTIVARIABLE CALCULUS (MATH 32A) FALL 2004 LECTURE NOTES 10/1/04 Office Hours: MS 7344, 11:00 12:40 Mon., Wed., Fri. E-mail: lchayes@math.ucla.edu Homework: 20% (each problem graded on a 2-pt. scale). PRINT OUT HOMEWORK FROM COURSE WEBPAGE Midterm
School: UCLA
A Brief Note on Proofs in Pure Mathematics Shagnik Das What is pure mathematics? Pure mathematics is a discipline that enjoys a rich history, dating back to Ancient Greece. The goal is to rigorously establish mathematical truths; to show with absolute cer
School: UCLA
Continuity of Functions Shagnik Das Introduction A general function from R to R can be very convoluted indeed, which means that we will not be able to make many meaningful statements about general functions. To develop a useful theory, we must instead res
School: UCLA
Mathematics 131a - A Short But Fairly Complete Study Guide For The Midterm Instructor: D.E.Weisbart Here are some points you should look over: (1) Know the logical connectives and quantiers, the truth tables for the quantiers, and how to negate statements
School: UCLA
Course: SYSTMS-DIFFNTL EQTN
Math 33B Time table: Lecture time Lecture 2 Lecture 3 Lecture location Midterm 1 Midterm 2 Final time 1111:50am MWF 4000A MS October 31st , Friday. November 24th , Wednesday lecture time, lecture room lecture time, lecture room December 13, 11:30am2:30pm
School: UCLA
Course: MULTIVARIABLE CALCULUS
Mathematica for Rogawski's Calculus 2nd Edition 2010 Based on Mathematica Version 7 Abdul Hassen, Gary Itzkowitz, Hieu D. Nguyen, Jay Schiffman W. H. Freeman and Company New York 2 Mathematica for Rogawski's Calculus 2nd Editiion.nb Copyright 2010 Mathem
School: UCLA
172C June 2013 AV, Asset Shares, Year by Year Financial Universal Life Account Values 1. For Universal Life UL policies in particular, the Account Value AV functions like a policy holder "bank account that is periodically updated Even though premium
School: UCLA
School: UCLA
Course: Introduction Of Complex Analysis
. ~o~.~H~ ~ ~ Q(i\'1+ r \ .)' v ~rJ1 OJ\ o~ c.~- &t H~b @-~6\ H(~\ ( \-\ Lt.-& H-o, ~\ ~c- \ i ' .f t.o 1f" 61. 1 ~"' .,_ d i:o ~'(t) ~ ~. e-'! - (u:l- 4. f.! 0 \ ' ~ ~ ~. ~ r:f l:-: .b. ~ +. H(-tj ~ ~ ~ ~ tt;tn.~ . ~; t '(:t\.:o \II C't- ~.,)'" _, Hl't\
School: UCLA
Course: Introduction Of Complex Analysis
-h cfw_; \ cfw_)'. sI . ~ I ~(.l. */ cfw_)1., ) ;: 7 : 1 ~ I( y )1. I d r;\ s :. f (,c, b)4 ( ~ (Y. '()- f ()l.,o) p( 'I ) - pcfw_)ll '() ')1. :. ~ (x, "f) . c l1.e. Palt\C-Mcfw__~/ tl f~" ~. ~\!JA\C(. . fr ~.q_._, 1]!.5' -. ~c r~J. Ml~ ~: J-t u ~ o. r
School: UCLA
Course: Introduction Of Complex Analysis
- t, c Lcfw_ - R /~ /k.-. cfw_ > t) ,:,2- ~. ~ itMJ( -R 0 aJf i = l z = -1 ~ CZr;.fv,4 t re~ R/ 1 ~) _:_ J=b )-+i~ ~t wJ)_ < - - 1 - RL-\ ~ ~ ;, ~ a. lTK ~ul ~ct ~ k ~ )~Jj eM;~, ~:Jt tr~v)~t>~.f 1tr1>'fl-o ~ 4' 7tJ \ Jj :=. ~t;> _!. -. dlr~ f'(~) f,l ~ -
School: UCLA
Course: ANALYSIS
Math 131a Lecture 2 Spring 2009 Midterm 1 Name: Instructions: There are 4 problems. Make sure you are not missing any pages. Unless stated otherwise (or unless it trivializes the problem), you may use without proof anything proven in the sections of the b
School: UCLA
Mathematics 131A Fall 2007 FINAL Your Name: Signature: INSTRUCTIONS: This is a closed-book test. Do all work on the sheets provided. If you need more space for your solution, use the back of the sheets and leave a pointer for the grader. Good luc
School: UCLA
Course: Probability Theory
Midterm 3, Math 170b - Lec 1, Winter 2013 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. Please raise your hand if you have questions at any time. The correct nal answer alone is n
School: UCLA
Course: Probability Theory
Midterm 2, Math 170b - Lec 1, Winter 2013 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. Please raise your hand if you have questions at any time. The correct nal answer alone is n
School: UCLA
Course: Probability Theory
Midterm 1 practice, Math 170b - Lec 1, Winter 2013 Instructor: Toni Antunovi c c Name and student ID: Question Points 1 10 2 10 3 10 4 10 5 10 Total: 50 Score 1. (a) (2 points) If is a sample space, what is P(). Solution: P() = 1 (b) (2 points) If P(A) =
School: UCLA
Math 32A: Practice Problems for Exam 2 Problem 1. A particle travels along a path r(t) with acceleration vector t4 , 4 t . Find r(t) if at t = 0, the particle is located at the origin and has initial velocity v0 = 2, 3 . Solution: We have r (t) = 1 1 t4 ,
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 3 c c From the textbook solve the problems 29, 30, 31, 32 and 33 from the Chapter 4. Solve the problems 1, 2, 4, 5 and 6 from the Chapter 4 additional exercises at http:/www.athenasc.com
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi c c Homework 1 From the textbook solve the problems 1, 2, 3, 5, 6, 8, 11 and 14 at the end of the Chapter 4. And also the problems below: Problem 1. Give examples of (not independent) random variab
School: UCLA
Course: Mathemtcl Modeling
Math 142-2, Homework 1 Solutions April 7, 2014 Problem 34.4 Suppose the growth rate of a certain species is not constant, but depends in a known way on the temperature of its environment. If the temperature is known as a function of time, derive an expres
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 4 c c solutions From the textbook solve the problems 42, 43 b) and 44 b), c) from the Chapter 4. Solve the problems 26, 27 and 29 from the Chapter 4 and problem 1 from the Chapter 7 addi
School: UCLA
Course: Introduction Of Complex Analysis
EE101 Engineering Electromagnetics Winter 2013 2/14/13 Homework #5 Due: Thursday Feb 21 10:00 AM Hand in to the TA at beginning of class. No late homework is accepted (see grading policy posted on eeweb). If you cannot make it to class, you must slip the
School: UCLA
Math32a HW1 Due on Monday, Jan 14 All the numbered problems are from the textbook Multivariable Calculus by Rogawski (2nd edition). Note: if your textbook is Early Transcendentals by Rogawski (2nd edition), then all your chapters are shifted by 1 down. Th
School: UCLA
Math 172 B Class Project 1 Object: to download a specific mortality table from the Society of Actuaries website and utilize mortality rates to calculate life expectancies Steps: 1. Log onto www.soa.org 2. At the bottom of the opening page, select popular
School: UCLA
Course: Linear Algebra
Math 33A, Sec. 2 Linear Algebra and Applications Spring 2012 Instructor: Professor Alan J. Laub Dept. of Mathematics / Electrical Engineering Math Sciences 7945 phone: 310-825-4245 e-mail: laub@ucla.edu Lecture: MWF 2:00 p.m. 2:50 p.m.; Rolfe 1200 Office
School: UCLA
Course: SYSTMS-DIFFNTL EQTN
Math 131 A/1: Analysis, UCLA, Spring 2015 Instructor name Dr. Roman Taranets, Department of Mathematics, UCLA E-mail: taranets @ math.ucla.edu Website: www.math.ucla.edu/~taranets Office Phone: (310) 825-4746 Office: MS 7360 Office Hours: MWF 9:00 am
School: UCLA
Course: SYSTMS-DIFFNTL EQTN
MATH 135-2 Instructor: Sungjin Kim, MS 6617A, E-mail: i707107@math.ucla.edu Meeting Time and Location: MWF 3:00 - 3:50 PM, Room: MS 5200 O ce Hours: MW 11:45 PM - 12:30 PM, Room: MS 6617A Textbook: G. Simmons, Dierential Equations (2nd) with Applications
School: UCLA
Course: Differential Equations
Math 33B, Differential Equations Lecture 1, Spring 2015 Instructor: Will Conley Email: wconley@ucla.edu Office: MS 6322 Office Hours: Tentatively Wednesdays 3:004:00 Thursdays 12:001:30 and 3:004:00, and by appointment Website: http:/www.math.ucla.edu/~wc
School: UCLA
Math 174E (Summer 2014) Mathematics of Finance Instructor: David W. Taylor Time/Location: MWR 11:00am-12:50pm in MS 5137. Text: Options, Futures, and Other Derivatives (8th edition) by John C. Hull. Instructor: David W. Taylor Oce Hours: TBA Email Address
School: UCLA
Math 174E, Lecture 1 (Winter 2014) Mathematics of Finance Instructor: David W. Taylor Time/Location: MWF 3:00pm-3:50pm in MS 5127. Text: Options, Futures, and Other Derivatives (8th edition) by John C. Hull. Instructor: David W. Taylor Oce Hours: Monday a
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 3 c c From the textbook solve the problems 29, 30, 31, 32 and 33 from the Chapter 4. Solve the problems 1, 2, 4, 5 and 6 from the Chapter 4 additional exercises at http:/www.athenasc.com
School: UCLA
Sule Ozler Economics 12 Fall 2011 READ THE EXPLANATIONS IN BOLD LETTERS CAREFULLY! MID-TERM EXAM - GOOD LUCK! WRITE YOUR NAME AND ID# You will not be allowed to ask questions during the exam. This exam has three sections. Each section has multiple questio
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi c c Homework 1 From the textbook solve the problems 1, 2, 3, 5, 6, 8, 11 and 14 at the end of the Chapter 4. And also the problems below: Problem 1. Give examples of (not independent) random variab
School: UCLA
Spring 2011- Professor Sule Ozler Name Economics 121 ID# MID-TERM EXAM-II WRITE YOUR NAME AND ID# This exam has TWO sections. Each section has multiple questions. Sections I is 40 points, section II is for a total of 60 points. I. MULTIPLE CHOICE: Choose
School: UCLA
Course: Mathemtcl Modeling
Math 142-2, Homework 1 Solutions April 7, 2014 Problem 34.4 Suppose the growth rate of a certain species is not constant, but depends in a known way on the temperature of its environment. If the temperature is known as a function of time, derive an expres
School: UCLA
Spring 2011- Professor Sule Ozler Name Economics 121 ID# FINAL EXAM WRITE YOUR NAME AND ID# No questions will be answered during the exam There will not be any bathroom breaks during the exam You are permitted to have only your writing equipment on your d
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 4 c c solutions From the textbook solve the problems 42, 43 b) and 44 b), c) from the Chapter 4. Solve the problems 26, 27 and 29 from the Chapter 4 and problem 1 from the Chapter 7 addi
School: UCLA
Course: ANALYSIS
Math 131a Lecture 2 Spring 2009 Midterm 1 Name: Instructions: There are 4 problems. Make sure you are not missing any pages. Unless stated otherwise (or unless it trivializes the problem), you may use without proof anything proven in the sections of the b
School: UCLA
Mathematics 131A Fall 2007 FINAL Your Name: Signature: INSTRUCTIONS: This is a closed-book test. Do all work on the sheets provided. If you need more space for your solution, use the back of the sheets and leave a pointer for the grader. Good luc
School: UCLA
Course: Probability Theory
Midterm 3, Math 170b - Lec 1, Winter 2013 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. Please raise your hand if you have questions at any time. The correct nal answer alone is n
School: UCLA
Course: Probability Theory
Midterm 2, Math 170b - Lec 1, Winter 2013 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. Please raise your hand if you have questions at any time. The correct nal answer alone is n
School: UCLA
Course: Probability Theory
Midterm 1 practice, Math 170b - Lec 1, Winter 2013 Instructor: Toni Antunovi c c Name and student ID: Question Points 1 10 2 10 3 10 4 10 5 10 Total: 50 Score 1. (a) (2 points) If is a sample space, what is P(). Solution: P() = 1 (b) (2 points) If P(A) =
School: UCLA
Math 32A: Practice Problems for Exam 2 Problem 1. A particle travels along a path r(t) with acceleration vector t4 , 4 t . Find r(t) if at t = 0, the particle is located at the origin and has initial velocity v0 = 2, 3 . Solution: We have r (t) = 1 1 t4 ,
School: UCLA
Course: MATH20F
Hector Ordorica Section: B51 / B02 TA: Matthew Cecil Exercise 3.1 Answer: D can be: 1. D = 0 0 00 2. D = 1 0 01 3. D = 0 1 10 Exercise 3.2 (a) Input: A = [1, 2, 0; 2, 1, 2; 0, 2, 1] B = [3, 0, 3; 1, 5, 1; 1, 1, 3] x = [1; 2; 3] C = (5*A^2*B - 3*A')^2 Outp
School: UCLA
Introduction to Probability 2nd Edition Problem Solutions (last updated: 11/25/11) c Dimitri P. Bertsekas and John N. Tsitsiklis Massachusetts Institute of Technology WWW site for book information and orders http:/www.athenasc.com Athena Scientific, Belmo
School: UCLA
Math 3C Midterm 1 Solutions Name: BruinID: Section: Read the following information before starting the exam. This test has six questions and seven pages. It is your responsibility to ensure that you have all of the pages! Show all work, clearly and in o
School: UCLA
Winter 2011- Professor Sule Ozler Name Economics 121 ID# FINAL EXAM WRITE YOUR NAME AND ID# This exam has three sections. Each section has multiple questions. Sections I and II are 20 points each, section III is for a total of 60 points. I. MULTIPLE CHOIC
School: UCLA
Course: MATH20F
Hector Ordorica Section: Tues 2-3 TA: Greene Exercise 2.1 (a) (b) (c) Input: C = [5 2 1; 6 0 1; 4 -6 2] d = [-1; 2; 3] x = C\d Output: x=0.9091 -1.0455 -3.4545 (d) Input: C*x-d Output: C*x-d ans = 1.0e-015 * -0.4441 -0.4441 0.8882 Exercise 2.2 Input: C =
School: UCLA
Course: Actuarial Math
MATH 115A - Practice Final Exam Paul Skoufranis November 19, 2011 Instructions: This is a practice exam for the nal examination of MATH 115A that would be similar to the nal examination I would give if I were teaching the course. This test may or may not
School: UCLA
School: UCLA
Course: Introduction Of Complex Analysis
EE101 Engineering Electromagnetics Winter 2013 2/14/13 Homework #5 Due: Thursday Feb 21 10:00 AM Hand in to the TA at beginning of class. No late homework is accepted (see grading policy posted on eeweb). If you cannot make it to class, you must slip the
School: UCLA
Math32a HW1 Due on Monday, Jan 14 All the numbered problems are from the textbook Multivariable Calculus by Rogawski (2nd edition). Note: if your textbook is Early Transcendentals by Rogawski (2nd edition), then all your chapters are shifted by 1 down. Th
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 3 c c From the textbook solve the problems 29, 30, 31, 32 and 33 from the Chapter 4. Solve the problems 1, 2, 4, 5 and 6 from the Chapter 4 additional exercises at http:/www.athenasc.com
School: UCLA
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 6 c c Solve the problems 18 a) c) d) e) and 19 from the Chapter 7 additional exercises at http:/www.athenasc.com/prob-supp.html And also the problems below: Problem 1. Denote points P0 ,
School: UCLA
Course: Mathemtcl Modeling
Math 142 Homework 1 Solution 34.5 (a) If the growth rate is 0, the discrete model becomes Nm+1 Nm = tfm , And the solution is Nm = N0 + t(f0 + f1 + fm1 ), which is analogous to integration, since let t = mt, then t t(f0 + f1 + fm1 ) f (s)ds 0 for t small
School: UCLA
Course: Mathemtcl Modeling
Math 142 Homework 2 Solution 34.16 We will rstly proceed similarly as 34.14(c). We assume the theoretical growth has the form N0 eR0 t , and we hope to gure out which N0 and R0 t the data best. 34.14(b) suggests that N0 should be equal to the initial popu
School: UCLA
MATH 32A FINAL EXAMINATION March 21th, 2012 Please show your work. You will receive little or no credit for a correct answer to a problem which is not accompanied by sucient explanations. If you have a question about any particular problem, please raise y
School: UCLA
Math 131A/2 Winter 2002 Handout #1a Instructor: E. Eros, MS 6931. Lecture Meeting Time: MWF 2:00PM-2:50PM Location: MS 5117 Recitation TA: to be announced, MS 5117 T 2:00P-2:50P Oce hours (tentative): TF 4-5. Text Fundamental Ideas of Analysis by Michael
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 5 c c From the textbook solve the problems 4 and 5 from the Chapter 5. Solve the problems 2, 4, 6, 7, 9 and 10 from the Chapter 7 additional exercises at http:/www.athenasc.com/prob-supp
School: UCLA
Course: 245abc
Math 202A Homework 13 Roman Vaisberg November 28, 2007 Problem 17. Suppose f is dened on R2 as follows: f (x, y ) = an if n x < n + 1 and n y < n + 1, (n 0); f (x, y ) = an if n x < n + 1 and n + 1 y < n + 2, (n 0); while f (x, y ) = 0 elsewhere. Here an
School: UCLA
INSTRUCTORS SOLUTIONS MANUAL A BRIEF COURSE IN MATHEMATICAL STATISTICS Elliot A. Tanis Hope College and Robert V. Hogg University of Iowa August 22, 2006 ii Contents Preface v 1 Probability 1.1 Basic Concepts . . . . . 1.2 Methods of Enumeration 1.3 Condi
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 2 c c From the textbook solve the problems 17, 18, 19, 22, 23 and 24 from the Chapter 4. Solve the problems 21, 22, 24, 30 from the Chapter 4 additional exercises at http:/www.athenasc.c
School: UCLA
Math 3C Midterm 2 Name: BruinID: Section: Read the following information before starting the exam. This test has six questions and fourteen pages. It is your responsibility to ensure that you have all of the pages! Show all work, clearly and in order, i
School: UCLA
Course: Probability Theory
Mathematics Department, UCLA P. Caputo Fall 08, midterm 1 Oct 22, 2008 Midterm 1: Math 170A Probability, Sec. 2 Last name First and Middle Names Signature UCLA ID number (if you are an extension student, say so) Please note: 1. Provide the information ask
School: UCLA
Course: Introduction Of Complex Analysis
EE101 Engineering Electromagnetics Winter 2013 1/24/12 Homework #3 Due: Thursday Jan 31 10:00 AM Hand in to the TA at beginning of class. No late homework is accepted (see grading policy posted on eeweb). If you cannot make it to class, you must slip the
School: UCLA
Course: 245abc
Math 245A Homework 2 Brett Hemenway October 19, 2005 Real Analysis Gerald B. Folland Chapter 1. 13. Every -nite measure is seminite. Let be a -nite measure on X, M. Since is -nite, there exist a sequence of sets cfw_En in M, with (En ) < and En = X . n=1
School: UCLA
Course: Mathemtcl Modeling
Math 142 Homework 0 Solution 32.11 The easier way: (slightly unrigorous, but its ne for this class) Suppose the bank compounds the interest n times a year, and let t := 1/n. With the additional deposit (or withdrawl) D (t), the balance at time t + t is gi
School: UCLA
Homework 4 Solutions Math 3C Due: Friday Nov 2, 9 a.m. #1(a) Let X be a random variable that equals the number of defective items in the sample. When the sampling is done with replacement, X is binomially distributed with parameters n = 5 and p = 5/20 = 1
School: UCLA
FINS3635 S2/2011 Put-Call Parity Matthias Thul Last Update: September 14, 2011 This documents shows you how a the general put-call relationship for European options can be obtained by simple no-arbitrage arguments and gives some examples of how it can be
School: UCLA
MATH 33A/2 PRACTICE MIDTERM 2 Problem 1. (True/False) . 1 1 1 Problem 2. Let v1 = 1 , v2 = 0 , v3 = 1 . 0 1 1 3 (a) Show that B = 1 , v2 , v3 ) is a basis for R . (v 1 (b) Let u = 1 . Find the coordinates of u with respect to the basis B. 2 (c) Find the c
School: UCLA
Course: 245abc
Math 245A Homework 1 Brett Hemenway October 19, 2005 3. a. Let M be an innite -algebra on a set X Let Bx be the intersection of all E M with x E . Suppose y Bx , then By Bx because Bx is a set in M which contains y . But Bx By because if y E for any E M,
School: UCLA
MATH 32A FIRST MIDTERM EXAMINATION October, 18th, 20101 Please show your work. You will receive little or no credit for a correct answer to a problem which is not accompanied by sufficient explanations. If you have a question about any particular problem,
School: UCLA
Course: MATH20F
Hector Ordorica 1/16/2007 Tues 2-3 Exercise 1.1 Input: H=8;e=5;c=3;t=20;o=15;r=18; O=15;r=18;d=4;o=15;r=18;i=9;c=3;a=1; HectorOrdorica = H + e + c + t + o + r + O + r + d + o + r + i + c + a Output: HectorOrdorica = 152 Exercise 1.2 Input: z = 25-(100-7ex
School: UCLA
Course: Discrete Math
Practice First Test Mathematics 61 Disclaimer: Listed here is a selection of the many possible sorts of problems. actual test is apt to make a different selection. 1. Let S5 be the set of all binary strings of length 5 (such as 11001). The Let E be
School: UCLA
Math 31A Midterm 1 Solutions 1. [3 points] The derivative of (a) 1 (b) (c) x2 x)2 x3 Brent Nelson is: 1 x2 1 2 x3 (3x 1 1 + x2 + 8x2 x + 3) (d) None of the above. Solution. We rst apply the quotient rule d dx x2 x)2 x3 = d d x3 dx [(x2 x)2 ] (x2 x)2 dx (
School: UCLA
Course: Mathemtcl Modeling
Math 142 Homework 1 Solution 32.3 (a) Use N (nt) to denote the population at time nt. Then for any n > 0, we have N (nt) = (1 + (b d)t)N (n 1)t) + 1000. (b) Given that N (0) = N0 , we hope to solve the equation above and get the general form for N (nt). T
School: UCLA
Management 1A Summer 2004 Danny S. Litt EXAM 2 SOLUTION Name: _ Student ID No. _ I agree to have my grade posted by Student ID Number. _ (Signature) PROBLEM 1 2 3 4 5 6 7 8 TOTAL POINTS 20 25 20 20 30 30 30 25 200 SCORE MANAGEMENT 1A Problem 1
School: UCLA
Name: Student ID: Section: 2 Prof. Alan J. Laub Math 33A MIDTERM EXAMINATION I Spring 2008 Instructions: Apr. 25, 2008 (a) The exam is closed-book (except for one page of notes) and will last 50 minutes. (b) Notation will conform as closely as possible to
School: UCLA
1008 C H A P T E R 16 M U LTI P L E I N T E G R AT I O N (ET CHAPTER 15) Therefore, D is defined by the inequalities 1 u uv Since x = v+1 and y = v+1 , we have y 2, x 3 y+x 6 y = v+1 = v u x v+1 uv and y+x = u u(v + 1) uv + = =u v+1 v+1 v
School: UCLA
Course: 31b
Math 31B, Lecture 4, Fall 2011 Exam #2, 9 November 2011 Name: ID Number: Section and TA: You have 50 minutes for the exam. No calculators, phones, notes, or books allowed. You must show your work for credit. Hint: n n=0 cr Question: 1 2 3 4 5 6 7 Tota
School: UCLA
S E C T I O N 17.1 Vector Fields (ET Section 16.1) 1061 19. F = x, 0, z SOLUTION This vector field is shown in (A) (by process of elimination). x x 2 + y2 + z2 , y x 2 + y2 + z2 , z x 2 + y2 + z2 20. F = SOLUTION The unit radial vector field i
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 4 c c From the textbook solve the problems 42, 43 b) and 44 b), c) from the Chapter 4. Solve the problems 26, 27 and 29 from the Chapter 4 and problem 1 from the Chapter 7 additional exe
School: UCLA
Course: Actuarial Math
MATH 115A - Assignment One - Solutions of Select Non-Graded Problems Paul Skoufranis October 3, 2011 1.2 Question 13) Let V denote the set of ordered pairs of real numbers. If (a1 , a2 ) and (b1 , b2 ) are elements of V and c R, dene (a1 , a2 ) + (b1 , b
School: UCLA
Course: Linear Algebra
Name: Student ID: Prof. Alan J. Laub June 9, 2011 Math 33A/1 FINAL EXAMINATION Spring 2011 Instructions: (a) The exam is closed-book (except for one two-sided page of notes) and will last two and a half hours. No calculators, cell phones, or other electro
School: UCLA
Chapter Review Exercises SOLUTION 811 The function whose value we want to approximate is f (x, y, z) = x 2 + y2 + z We use the linear approximation at the point (7, 5, 70), hence h = 7.1 - 7 = 0.1, k = 4.9 - 5 = -0.1, and l = 70.1 - 70 = 0.1. We g
School: UCLA
MULTIVARIABLE CALCULUS (MATH 32A) FALL 2004 LECTURE NOTES 10/1/04 Office Hours: MS 7344, 11:00 12:40 Mon., Wed., Fri. E-mail: lchayes@math.ucla.edu Homework: 20% (each problem graded on a 2-pt. scale). PRINT OUT HOMEWORK FROM COURSE WEBPAGE Midterm
School: UCLA
A Brief Note on Proofs in Pure Mathematics Shagnik Das What is pure mathematics? Pure mathematics is a discipline that enjoys a rich history, dating back to Ancient Greece. The goal is to rigorously establish mathematical truths; to show with absolute cer
School: UCLA
Continuity of Functions Shagnik Das Introduction A general function from R to R can be very convoluted indeed, which means that we will not be able to make many meaningful statements about general functions. To develop a useful theory, we must instead res
School: UCLA
Mathematics 131a - A Short But Fairly Complete Study Guide For The Midterm Instructor: D.E.Weisbart Here are some points you should look over: (1) Know the logical connectives and quantiers, the truth tables for the quantiers, and how to negate statements
School: UCLA
Mathematics 131a - A Short But Fairly Complete Study Guide For The Final Instructor: D.E.Weisbart Here are some points you should look over: (1) Know the logical connectives and quantiers, the truth tables for the quantiers, and how to negate statements.
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Theorem: For a simple graph, any two of these three statements, taken together, imply the third: The graph is connected. The graph is acyclic. The number of vertices in the graph is exactly one more than the number of edges. Proof: By induction. In a grap
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Course: Math 164
Math 164: Optimization Nonlinear optimization with equality constraints Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 material taken from the textbook Chong-Zak, 4th Ed. online discussions on piazza.com we discuss how to recognize a s
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Course: Math 164
Math 164: Optimization The Simplex method Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 material taken from the textbook Chong-Zak, 4th Ed. online discussions on piazza.com Overview: idea and approach If a standard-form LP has a solut
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Course: Math 164
Math 164: Optimization Krylov subspace, nonlinear CG, and preconditioning Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 material taken from the textbook Chong-Zak, 4th Ed., and the CG paper by Shewchuk online discussions on piazza.com
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Course: Math 164
Math 164: Optimization Algorithms for constrained optimization Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 material taken from the textbook Chong-Zak, 4th Ed. online discussions on piazza.com Coverage We will learn some algorithms fo
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Course: Math 164
Introduction to Optimization Major subfields Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 online discussions on piazza.com Overview Continuous vs Discrete Continuous optimization: convex vs non-convex unconstrained vs constrained l
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Course: Math 164
Math 164: Optimization Nonlinear optimization with inequality constraints Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 material taken from the textbook Chong-Zak, 4th Ed. online discussions on piazza.com we discuss how to recognize a
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Course: Math 164
Math 164: Optimization Basics of Optimization Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 based on Chong-Zak, 4th Ed. online discussions on piazza.com Goals of this lecture For a general form minimize f (x) subject to x we study the
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Course: Math 164
Math 164: Optimization Netwons Method Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 some material taken from Chong-Zak, 4th Ed. online discussions on piazza.com Main features of Newtons method Uses both first derivatives (gradients) a
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Course: Math 164
Math 164: Optimization Linear programming Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 material taken from the textbook Chong-Zak, 4th Ed. online discussions on piazza.com History The word programming used traditionally by planners t
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Course: Math 164
Math 164: Optimization Barzilai-Borwein Method Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 online discussions on piazza.com Main features of the Barzilai-Borwein (BB) method The BB method was published in a 8-page paper1 in 1988 It
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Course: Math 164
Math 164: Optimization Conjugate direction methods Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 material taken from the textbook Chong-Zak, 4th Ed., and the CG paper by Shewchuk online discussions on piazza.com Main features of conjug
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Course: Math 164
Math 164: Optimization Gradient Methods Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 some material taken from Chong-Zak, 4th Ed. online discussions on piazza.com Main features of gradient methods They are the most popular methods (in
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Course: Math 164
Math 164: Optimization One-Dimensional Search Methods Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 based on Chong-Zak, 4th Ed. online discussions on piazza.com Goal of this lecture Develop methods for solving the one-dimensional probl
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Course: Math 164
Math 164: Optimization Optimization application examples Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 online discussions on piazza.com Job assignment problem1 An insurance oce handles three types of work: Information, Policy, Claims.
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Course: Math 164
Math 164: Optimization Support vector machine Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 online discussions on piazza.com Support vector machine (SVM) Background: to classify a set of data points into two sets. Examples: emails: le
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Course: Math 164
Math 164: Introduction to Optimization Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 online discussions on piazza.com Resource-constrained revenue optimization m resources; resource i has bi units available n products; product j uses
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Course: Math 164
Math 164: Introduction to Optimization Instructor: Wotao Yin Department of Mathematics, UCLA Spring 2015 online discussions on piazza.com What is mathematical optimization? Optimization models the goal of solving a problem in the optimal way. Examples:
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Realdata Prediction (valueofr) t N 0.36 0.365 0.37 0.375 0.38 0.385 0.39 0.395 0.4 0.405 0.41 0.415 0.42 0.425 0.43 0 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1 1500 1433.32941 1440.51401 1447.73461 1454.99141 1462.2
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Stepsforsolving0.5*sinh(x)=x xl xmid xr f(xmid) 2 2.5 3 0.52510224 2 2.25 2.5 0.09558415 2 2.125 2.25 0.06163387 2.125 2.1875 2.25 0.01267652 2.125 2.15625 2.1875 0.02551915 2.15625 2.171875 2.1875 0.00668563 2.171875 2.1796875 2.1875 0.00292884 2.171875
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Temperature (deg. F) 0 5 10 15 20 25 30 35 40 45 50 Wind Speed (mph) 3 6 9 12 -6.88019642 -11.879 -15.07066 -17.46409 -1.22442594 -5.924347 -8.925181 -11.17551 4.431344549 0.0303024 -2.779701 -4.886925 10.08711503 5.9849522 3.365779 1.4016585 15.74288552
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Course: Math 170
Probability Theory, Math 170b, Spring 2015, Toni Antunovi c c Homework 4 Due Friday, April 24th From the books supplementary problems, solve problems 2, 4, 5, 6 in Chapter 4 (see http:/www.athenasc.com/prob-supp.html). And also the problems below: Problem
School: UCLA
Course: Math 170
Introduction to Probability 2nd Edition Problem Solutions (last updated: 10/22/13) c Dimitri P. Bertsekas and John N. Tsitsiklis Massachusetts Institute of Technology WWW site for book information and orders http:/www.athenasc.com Athena Scientic, Belmont
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Course: Math 170
Midterm 2, Math 170b - Practice 2 solutions Name and student ID: Question Points 1 10 2 10 3 10 4 10 Total: 40 Score 1. (a) (2 points) You roll a fair die N times where N is Poisson with parameter 1. What is the expected value of the sum of the outcomes?
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Course: Math 170
Probability Theory, Math 170b, Spring 2015, Homework 7 due Friday, May 15th Solve the problems 10, 11, 13, 15, 17 and 18 from the Chapter 7 additional exercises at http:/www.athenasc.com/prob-supp.html And also the problems below: Problem 1. Let X1 , X2 ,
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Course: Math 170
Midterm 2, Math 170b - Practice 2 Name and student ID: Question Points 1 10 2 10 3 10 4 10 Total: 40 Score 1. (a) (2 points) You roll a fair die N times where N is Poisson with parameter 1. What is the expected value of the sum of the outcomes? (b) (2 poi
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Course: Math 170
Midterm 2, Math 170B - Practice 1 Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. Please raise your hand if you have questions at any time. The correct nal answer alone is not su cient for full credit - try to e
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Course: Math 170
Midterm 2 practice, Math 170b, Spring 2015 Name and student ID: Question Points 1 10 2 10 3 10 4 10 Total: 40 Score 1. (a) (2 points) Can a random variable have the same PDF and CDF? Justify your reasoning. (b) (2 points) Does there exist a random variabl
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Course: Math 170
Midterm 2, Math 170B - Practice 1 solutions Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. Please raise your hand if you have questions at any time. The correct nal answer alone is not sucient for full credit -
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Course: Math 170
Probability Theory, Math 170b, Spring 2015, Toni Antunovi c c Homework 6 Due Friday, May 8th From the books supplementary problems, solve problems 5, 6, 7, 9 and 19 in Chapter 7 (see http:/www.athenasc.com/prob-supp.html). And also the problems below: Pro
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Course: Math 33B
Math 33B: Dierential Equations Homework 4: Introduction to second order linear ODEs Due on: Fri., May 1, 2015 - 11:00 am Instructor: aliki Please include your name, UID and discussion section on the submitted homework. Problem 1 Consider the following in
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Course: Math 33B
REVIEW 9 Introduction to second order linear ODEs 9.1 9.2 9.3 9.4 Standard form . . . . . . . . . . . . Structure of the general solution . . Wronskian determinant . . . . . . . Existence & uniqueness of solutions . . . . . . . . . . . . . . . . . . . . .
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Course: Math 33B
Math 33B: Dierential Equations Practice examples 10: Fundamental solutions to 2nd order LODEs1 April 2015 Instructor: aliki m. Given the following initial value problem y 3y + 2y = 0, y(0) = 1, y (0) = 0, show that y1 = e2x and y2 = ex are linearly indepe
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Course: Math 33B
REVIEW 8 Autonomous dierential equations & stability 8.1 8.2 8.3 8.4 Denitions . . . . . . . . . . . . Qualitative solutions . . . . . . Logistic growth example . . . . Classication of critical points . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Course: Math 33B
Math 33B: Dierential Equations Practice examples 9: Autonomous ODEs Instructor: aliki m. Qualitative behavior of autonomous ODEs A model for the population y(t) in a city is given by the following initial-value problem, dy = y(a by), y(0) = 5000, dt (1) w
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Course: Math 33B
REVIEW 7 Existence & uniqueness of solutions 7.1 7.2 7.3 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Existence & uniqueness theorems . . . . . . . . . . . . . . . . . Applying the theorems to IVPs . . . . . . . . . . . . . . . .
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Course: Math 33B
Math 33B: Dierential Equations Practice examples 8: Existence & uniqueness theorems April 2015 Instructor: aliki m. Question 1 Determine whether the following initial-value problem 1 dy = ln(y), x dx y(1) = e, (1) is guaranteed to have a unique solution.
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Course: Math 33B
Math 33B: Dierential Equations Homework 3: Existence and uniqueness of IVPs & Autonomous equations Due on: Fri., Apr. 24, 2015 - 11:00 AM : Instructor: aliki m. Please include your name, UID and discussion section on the submitted homework. Problem 1 Whic
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Course: SYSTMS-DIFFNTL EQTN
Math 33B Time table: Lecture time Lecture 2 Lecture 3 Lecture location Midterm 1 Midterm 2 Final time 1111:50am MWF 4000A MS October 31st , Friday. November 24th , Wednesday lecture time, lecture room lecture time, lecture room December 13, 11:30am2:30pm
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Course: MULTIVARIABLE CALCULUS
Mathematica for Rogawski's Calculus 2nd Edition 2010 Based on Mathematica Version 7 Abdul Hassen, Gary Itzkowitz, Hieu D. Nguyen, Jay Schiffman W. H. Freeman and Company New York 2 Mathematica for Rogawski's Calculus 2nd Editiion.nb Copyright 2010 Mathem
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172C June 2013 AV, Asset Shares, Year by Year Financial Universal Life Account Values 1. For Universal Life UL policies in particular, the Account Value AV functions like a policy holder "bank account that is periodically updated Even though premium
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School: UCLA
Course: Introduction Of Complex Analysis
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School: UCLA
Course: Introduction Of Complex Analysis
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Course: Introduction Of Complex Analysis
- t, c Lcfw_ - R /~ /k.-. cfw_ > t) ,:,2- ~. ~ itMJ( -R 0 aJf i = l z = -1 ~ CZr;.fv,4 t re~ R/ 1 ~) _:_ J=b )-+i~ ~t wJ)_ < - - 1 - RL-\ ~ ~ ;, ~ a. lTK ~ul ~ct ~ k ~ )~Jj eM;~, ~:Jt tr~v)~t>~.f 1tr1>'fl-o ~ 4' 7tJ \ Jj :=. ~t;> _!. -. dlr~ f'(~) f,l ~ -
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Course: Introduction Of Complex Analysis
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Course: Introduction Of Complex Analysis
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Course: SYSTMS-DIFFNTL EQTN
to bifurcation theory Introduction John David Crawford Institute for Fusion Studies, The University of Texas at Austin, Austin, Texas 78712 and Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, Pennsylvania 15280 The theory of bif
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Course: Math 31 B Lecture 4
Module 4: Neural and Hormonal Systems Overview: What We Have in Mind Building blocks of mind: Neurons and how they communicate (neurotransmi9ers) Systems that build the mind: Func=ons of Parts of the Nervous system Suppor
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Course: Math 31 B Lecture 4
Module 18: Vision, and Perceptual Organiza9on and Interpreta9on Vision: Energy, Sensa,on, and Percep,on The Visible Spectrum We encounter waves of electromagne2c radia2on. Our eyes respond to some of these waves. Our brain turns these
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Course: Math 31 B Lecture 4
Module 1: The Story of Psychology From specula9on to science: The Birth of Modern Psychology Aristotle (4th century BCE) asked ques9ons to understand the rela9onship between body and psyche. His way of answering those ques9ons
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Course: Math 31 B Lecture 4
Module 13: Developmental Issues, Prenatal Development, and the Newborn nature and nurture How do genes and experience guide development over our lifespan? change and stability Issues in Developmental Psychology con?nuity vs. stages In wh
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Course: Math 31 B Lecture 4
Module 7: Brain States and Consciousness What is Consciousness, Exactly? alertness; being awake vs. being unconscious self-awareness; the ability to think about self having free will; being able to make a conscious decision a pe
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Course: Math 31 B Lecture 4
Solutions to practice midterm 2 Sudesh Kalyanswamy and Jiayin Guo (1) From the problem we know k = 0.25 while N = 5000, and we are going to solve dy y = ky(1 ), dt N with initial value y(0) = 1. Since y(0) = 1, this means ky(1 separate the variables to g
School: UCLA
Course: Math 31 B Lecture 4
not the same, so no . k=1 k=2 for different values of k, you get anther solution. y=k(t+1) +6 is a "family" of solutions y(0)=8 - - - - - PG corrections, I "lost " a negative when we took the antiderivative .
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Course: Math 31 B Lecture 4
Math 3B Lecture 1 Winter 2015 due Friday March 6 Late homework is NOT accepted . at 8 am . HW # 7 Name _ Section A B C D (circle one ) UCLA ID # _ Print this page and staple it to your homework papers . 6.1 # 23-27,28-31,35 6.2 # 30,36,40 6.3 # 2,8,14,26
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Course: Math 31 B Lecture 4
Math 3B Lecture 1 Winter 2015 due Monday Feb 23 Late homework is NOT accepted . at 8 am . HW # 5 Name _ Section A B C D (circle one ) UCLA ID # _ Print this page and staple it to your homework papers . 5.6 #11,12,16,17,20,39 ( during eighth year means bet
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Course: Math 31 B Lecture 4
Math 3B Lecture 1 Winter 2015 due Friday Feb 27 Late homework is NOT accepted . at 8 am . HW # 6 Name _ Section A B C D (circle one ) UCLA ID # _ Print this page and staple it to your homework papers . 6.1 #1,3,7,10,14,16,19-22,39 6.2 # 1,5,8,12,17,21,24
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Course: Math 31 B Lecture 4
Math 3B Lecture 1 Winter 2015 due Wednesday February 17 at 8 am . Late homework is NOT accepted . HW # 4 Name _ Section A B C D (circle one ) UCLA ID # _ Print this page and staple it to your homework papers . Practice 5.4 # 1,5,11,15,17,27 5.5 # 1,3,7,11
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Course: Math 31 B Lecture 4
A few solutions to Prof. Greenes practice midterm 1 Sudesh Kalyanswamy (8) (a) The graph of y = 36 x2 is shown below in gure 1. Figure 1: The graph of f (x) = 36 x2 It is the top half of a circle of radius 6. The portion between x = 0 and x = 6 is the rig
School: UCLA
Course: Math 31 B Lecture 4
Math 3B Lecture 1 Winter 2015 NOT accepted . due Friday Feb 6 at 8 am . Late homework is HW # 3 Name _ Section A B C D (circle one ) UCLA ID # _ 4.3 # 24,26,38,44 4.5 # 35,41 5.1 #9,17,22,26,29 5.2 # 2,8,14,19,20,22,24,30 Chapter 4 review # 2,3,7,15,20 Tu
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Course: Math 31 B Lecture 4
Math 3B Lecture 1 Winter 2015 NOT accepted . due Friday January 23 at 8 am . Late homework is HW # 2 Name _ Section A B C D (circle one ) UCLA ID # _ 4.3 # 16,17,28,35,42 1.7 # 13,19,21,24,31,32 4.5 # 1-4,9,10,13,14,15,17,21,22 Turn in all of these proble
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Course: Math 31 B Lecture 4
Math 3B Lecture 1 Winter 2015 NOT accepted . due Friday January 16 at 8 am . Late homework is Name _ Section A B C D (circle one ) UCLA ID # _ "Practice problems"are for you to practice your skills. These are NOT collected . "Turn in problems" must be wri
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Course: Math 31 B Lecture 4
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School: UCLA
Course: Math 31 B Lecture 4
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Course Information The Denite Integral Math 3B/1 UCLA April 1st, 2013 Course Information This is Math 3B, Lecture 1. I am your host, George J. Schaeer. The course website is http:/www.math.ucla.edu/gschae/3b.1.13s/ Please read the entire course informatio
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Applications of Integration Subsitution Math 3B/1 UCLA George J. Schaeer April 10th, 2013 Areas between curves 3 2 1 -5 -4 -3 -2 -1 0 1 2 3 4 5 -1 -2 If f and g are integrable on [a, b] and f (x) g(x) whenever x [a, b], the area of the region bounded by y
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The Fundamental Theorem of Calculus Math 3B/1 UCLA George J. Schaeer April 5th, 2013 More, more, more! Last time we thought about how to integrate functions describing shapes we know and love from geometry. a 0 r a k dx = ka 0 x dx = 1 a2 2 But we are not
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The Denite Integral Math 3B/1 UCLA George J. Schaeer April 4th, 2013 Obviously. You should always read the relevant section in your textbook concurrent with lecture. This will help you with the homework! The relevant section for this and Mondays lecture i
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Integration by Subsitution Integration by Parts Math 3B/1 UCLA George J. Schaeer April 15th, 2013 Announcements HW1 has been graded. The grades are on my.ucla.edu, they will be returned in discussion (assuming your TAs remember!). TA oce hours: Cassidy: T
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Fundamental Theorem of Calculus Applications of Integration Math 3B/1 UCLA George J. Schaeer April 8th, 2013 Integration For SCIENCE we want to solve denite integrals like b f (x) dx a We have seen three ways to integrate: Approximate with Riemann sums an
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Integration by Subsitution Math 3B/1 UCLA George J. Schaeer April 12th, 2013 Last time Last time we evaluated the indenite integral cos(5x) dx By substituting u = 5x and du = 5 dx, so dx = cos(5x) dx = 1 1 cos(u) du = 5 5 = Check your work! 1 5 du. cos(u)
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Mathematics 174E: Lecture 1 David Wihr Taylor UCLA, Los Angeles January 6, 2014 David Wihr Taylor Mathematics 174E: Lecture 1 UCLA, Los Angeles Course Description This course is a mathematical nance course. Courses with similar titles are oered in other d
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Mathematics 174E: Lecture 7: Mechanics of Futures Markets and No Arbitrage David Wihr Taylor UCLA, Los Angeles January 17, 2014 David Wihr Taylor Mathematics 174E: Lecture 7: Mechanics of Futures Markets and No Arbitrage UCLA, Los Angeles Closing Out Posi
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Basics Independence Mathematics 174E: Lecture 3: Discrete Random Walks David Wihr Taylor (based on lecture notes by R. Caisch) UCLA, Los Angeles January 10, 2014 David Wihr Taylor (based on lecture notes by R. Caisch) Mathematics 174E: Lecture 3: Discrete
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UCLA Math 174EExam #2Fall, 2013 1 1. (20 points) This problem has parts (a) and (b) (a) (8 points) What are the two characteristic properties of a Wiener process? (b) (12 points) A quantity Q obeys a law dQ = 3dt + 3dx, where dx is a generalized Wiener pr
School: UCLA
Introduction to Probability 2nd Edition Problem Solutions (last updated: 10/22/13) c Dimitri P. Bertsekas and John N. Tsitsiklis Massachusetts Institute of Technology WWW site for book information and orders http:/www.athenasc.com Athena Scientic, Belmont
School: UCLA
Course: Algebraic Topology
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School: UCLA
Course: Algebraic Topology
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School: UCLA
Course: Algebraic Topology
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School: UCLA
Course: Algebraic Topology
A D SG A x x WEB 5 5 7 x 7 A A R3 H 3: 1 2 B D R R3 BD BD 1 ; 1 2 1 ; B D 3 3 ; 1 2 ; B D 3 2 2 g: B 2 BD 2 3 3 D 4 7 5; 1 1 :2 ; :2 1 1; 3 2 3 1 D 4 65 7 3 2 D 1 D 1 1 2 H B D f 1; 2 D 4 8 5; 6 1 B: B 2 H 3 1 2 D4 2 D4 2 ; 3 1 ; 5 3 1 4 5; 3 3 3 2 5; 4
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Course: Algebraic Topology
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School: UCLA
Course: Algebraic Topology
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School: UCLA
Course: Algebraic Topology
B D f 1; : : : ; D c1 1 C C cp pg H c1 ; : : : ; cp B Rp 2 3 c1 6 : 7 B D 4 : 5 : p; H cp 1 H D H B 2 3 3 D 465 2 f 1; 2g 2 2 3 1 D 4 05 1 1 B B 2 3 3 D 4 12 5 7 2 B H c1 2 3 2 3 2 3 3 1 3 4 6 5 C c2 4 0 5 D 4 12 5 c1 2 1 7 c2 2 3 1 3 0 12 5 1 7 2 B D 3
School: UCLA
Course: Algebraic Topology
A 2 1 A D4 2 3 32 3 2 3 5 7 0 7 54 3 5 D 4 0 5 3 2 0 1 0 5 A: A A D 2 1 4 2 3 1 0 5 3 7 35 2 5 7 3 A D 2 1 40 0 3 7 17 5 19 1 5 2 3 8 12 2 1 40 0 1 2 0 3 7 17 5 49 5 3 0 A A A x2 D 0; x3 D 0; A D .x1 ; x2 ; x3 /; A D .1; 0; 0/: A A A n n A A A D x1 A A Rn
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Course: Algebraic Topology
2 Rn ; ; H H; c 1; : : : ; H C H c f 1; : : : ; n R ; p 3 63 6 AD4 0 6 2 3 60 6 40 0 1 pg p m 1 1 3 3 3 3 9 9 1 2 0 0 3 6 0 0 0 0 1 0 n n 3 A 3 A 3 Rm : n 3 8 27 7 45 6 3 6 47 7 25 0 1 0 1 2 3 A A Rn A 3 A Rn H 3 H B AD f 1; : : : ; p g A B A: 1; : : : ;
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Course: Algebraic Topology
Rn R2 2 R H H H H H 2 3 2 4 85 1 D 6 2 3 6 D 4 10 5; 11 2 2 3 3 D 4 85 7 AD 3 1 2 3 4 D 4 65 7 2 f 1; 3 : 3g 2; A A 2 3 2 3 2 2 4 0 5; 4 3 5; 1 D 2 D 6 3 2 3 6 D 4 15 17 1 2 3 A 3 2 3 0 D 4 5 5; 5 A 2 3 5 D 4 55 3 A A p 2 Rp 3 AD4 9 9 2 1 6 4 6 AD6 5 6 4
School: UCLA
Course: Algebraic Topology
B A A A D A B A D B D A B AD 1 2 1 6 2 6 5D4 2 3 2 B 3 2 3 4 3 2 0 1 2 8 7 11 3 9 27 7 15 8 A A 3 D 3 1 C2 2 4 3 D 3 D5 1 1 C2 2 2 4 D5 1 2 3 A 1 1 2 2 f 1; 5 f 1; 5 5g 2; 4 2; 5g f 1; A A 2; 5g A A A B A B A 2 1 AD4 2 3 1 0 5 2 0 A D 40 0 SG n A 1 0 0 n
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Course: Algebraic Topology
A D A A A A D A A n Rn A m n Rn n A D C c.A / D c. / D m A D A. C / D A C A D A D Rn Rn A A D A A D Rn A D C c A A C A A D A c; A.c / D A A A A A A A D Rn H x3 H H Rn n n Rn e3 e2 x2 1 e1 n n 2 3 1 607 D 6 : 7; 4:5 : 0 x1 f 1; : : : ; R3 ng A A 2 2 3 0 61
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Course: Algebraic Topology
D x R D R3 x 60 T D.R. / D R.D. / T R R 2 4 y R D 4 z e3 T e2 e1 A1 y x A2 2 A1 D 4 2 1 ' ' 0 A2 D 4 0 0 3 0 05 1 0 0 ' ' 4 R3 30 D .5; 2; 1/ 3 0 05 1 1 0 4 S .2; 2; 6/ S .1; 2; 1/ R2 .4:2; 1:2; 4/ .6; 4; 2/ S .0; 0; 10/ .7; 3; 5/ .12; 8; 2/ S .0; 0; 10/
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Course: Algebraic Topology
Rn A D A 2 3 AD4 1 2 2 1 40 0 A 2 0 0 0 1 0 1 2 0 6 2 4 3 7 15 4 x1 A D 3 3 0 2 0 5; 0 0 x1 D 2x2 C x4 2 1 3 8 2x2 1 2 5 3x5 x3 D x4 C 3x5 D 0 x3 C 2x4 2x5 D 0 0D0 2x4 C 2x5 3 2 3 2 3 2 x1 2x2 C x4 3x5 2 6 x2 7 6 7 617 6 x2 6 7 6 7 6 7 6 6 x3 7 D 6 2x4 C
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Course: Algebraic Topology
Rn 1 2 x2 1 1 2 L L v1 v2 x1 uv u , v2 ncfw_v 1 Spa 2w w v L 1 2 Dk L u v is not on L 1 2w is not on L Rn 1; : : : ; p 1; : : : ; p n R f 1; : : : ; 1; : : : ; p pg Rn Rn Rn A A A AD 1 f 1; : : : ; ng Rm A x3 A m n Rm A Rm 1 AD4 4 3 A Col A b Rm 2 x2 0 n
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Course: Algebraic Topology
. 30 / D p . 30 / D 3=2 2 1 40 0 D . 2; 6/ :5 p 32 p p 3 32 2 3=2 1=2 0 1 0 2 p 6 54 1=2 65 3=2 0 54 0 1 1 0 0 1 0 0 1 p 2p 3 3=2 1=2 p3 5 p D 4 1=2 3=2 3 3C55 0 0 1 0 1 0 Rn Rn A; A D Rn H Rn H H x3 H c C H c H v1 v2 x1 0 x2 1 Rn 2 2g D s1 c C f 1; C 1 C
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Course: Algebraic Topology
4 4 4 4 R2 3 30 3 x2 x2 x2 p (a) Original figure. p x1 (b) Translated to origin by p. p x1 (c) Rotated about the origin. 3 x1 (d) Translated back by p. 45 x R2 DD A 4 0 3 2 2 45 5 3 y x 60 .2; 1/ . 1; 4/ 90 100 B x .6; 8/ 45 3 2 y x2 p x1 3 . 2; 6/ .3; 7/
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Course: Algebraic Topology
D . 6; 4; 5/ 3 z 3 e3 y 2 x . p 3 30 / D .:5; 0; 3=2/ 30 ; 0; 2p 3=2 4 0 :5 0 1 0 3 :5 5 p0 3=2 2p 3=2 6 0 AD6 4 :5 0 0 1 0 0 :5 p0 3=2 0 e1 x p 1 30 / D . 3=2; 0; :5/ 30 ; 0; . e2 y .x; y; ; 1/ .x 2 1 60 6 40 0 6; y C 4; C 5; 1/ 3 0 0 6 1 0 47 7 0 1 55
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Course: ANALYSIS
Math 131a Lecture 2 Spring 2009 Midterm 1 Name: Instructions: There are 4 problems. Make sure you are not missing any pages. Unless stated otherwise (or unless it trivializes the problem), you may use without proof anything proven in the sections of the b
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Mathematics 131A Fall 2007 FINAL Your Name: Signature: INSTRUCTIONS: This is a closed-book test. Do all work on the sheets provided. If you need more space for your solution, use the back of the sheets and leave a pointer for the grader. Good luc
School: UCLA
Course: Probability Theory
Midterm 3, Math 170b - Lec 1, Winter 2013 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. Please raise your hand if you have questions at any time. The correct nal answer alone is n
School: UCLA
Course: Probability Theory
Midterm 2, Math 170b - Lec 1, Winter 2013 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. Please raise your hand if you have questions at any time. The correct nal answer alone is n
School: UCLA
Course: Probability Theory
Midterm 1 practice, Math 170b - Lec 1, Winter 2013 Instructor: Toni Antunovi c c Name and student ID: Question Points 1 10 2 10 3 10 4 10 5 10 Total: 50 Score 1. (a) (2 points) If is a sample space, what is P(). Solution: P() = 1 (b) (2 points) If P(A) =
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Math 32A: Practice Problems for Exam 2 Problem 1. A particle travels along a path r(t) with acceleration vector t4 , 4 t . Find r(t) if at t = 0, the particle is located at the origin and has initial velocity v0 = 2, 3 . Solution: We have r (t) = 1 1 t4 ,
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Math 3C Midterm 1 Solutions Name: BruinID: Section: Read the following information before starting the exam. This test has six questions and seven pages. It is your responsibility to ensure that you have all of the pages! Show all work, clearly and in o
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Course: Actuarial Math
MATH 115A - Practice Final Exam Paul Skoufranis November 19, 2011 Instructions: This is a practice exam for the nal examination of MATH 115A that would be similar to the nal examination I would give if I were teaching the course. This test may or may not
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MATH 32A FINAL EXAMINATION March 21th, 2012 Please show your work. You will receive little or no credit for a correct answer to a problem which is not accompanied by sucient explanations. If you have a question about any particular problem, please raise y
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Math 3C Midterm 2 Name: BruinID: Section: Read the following information before starting the exam. This test has six questions and fourteen pages. It is your responsibility to ensure that you have all of the pages! Show all work, clearly and in order, i
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Course: Probability Theory
Mathematics Department, UCLA P. Caputo Fall 08, midterm 1 Oct 22, 2008 Midterm 1: Math 170A Probability, Sec. 2 Last name First and Middle Names Signature UCLA ID number (if you are an extension student, say so) Please note: 1. Provide the information ask
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MATH 33A/2 PRACTICE MIDTERM 2 Problem 1. (True/False) . 1 1 1 Problem 2. Let v1 = 1 , v2 = 0 , v3 = 1 . 0 1 1 3 (a) Show that B = 1 , v2 , v3 ) is a basis for R . (v 1 (b) Let u = 1 . Find the coordinates of u with respect to the basis B. 2 (c) Find the c
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MATH 32A FIRST MIDTERM EXAMINATION October, 18th, 20101 Please show your work. You will receive little or no credit for a correct answer to a problem which is not accompanied by sufficient explanations. If you have a question about any particular problem,
School: UCLA
Course: Discrete Math
Practice First Test Mathematics 61 Disclaimer: Listed here is a selection of the many possible sorts of problems. actual test is apt to make a different selection. 1. Let S5 be the set of all binary strings of length 5 (such as 11001). The Let E be
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Math 31A Midterm 1 Solutions 1. [3 points] The derivative of (a) 1 (b) (c) x2 x)2 x3 Brent Nelson is: 1 x2 1 2 x3 (3x 1 1 + x2 + 8x2 x + 3) (d) None of the above. Solution. We rst apply the quotient rule d dx x2 x)2 x3 = d d x3 dx [(x2 x)2 ] (x2 x)2 dx (
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Management 1A Summer 2004 Danny S. Litt EXAM 2 SOLUTION Name: _ Student ID No. _ I agree to have my grade posted by Student ID Number. _ (Signature) PROBLEM 1 2 3 4 5 6 7 8 TOTAL POINTS 20 25 20 20 30 30 30 25 200 SCORE MANAGEMENT 1A Problem 1
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Course: 31b
Math 31B, Lecture 4, Fall 2011 Exam #2, 9 November 2011 Name: ID Number: Section and TA: You have 50 minutes for the exam. No calculators, phones, notes, or books allowed. You must show your work for credit. Hint: n n=0 cr Question: 1 2 3 4 5 6 7 Tota
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Course: Linear Algebra
Name: Student ID: Prof. Alan J. Laub June 9, 2011 Math 33A/1 FINAL EXAMINATION Spring 2011 Instructions: (a) The exam is closed-book (except for one two-sided page of notes) and will last two and a half hours. No calculators, cell phones, or other electro
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Management 1A Summer 2004 Danny S. Litt EXAM 1 SOLUTION Name: _ Student ID No. _ I agree to have my grade posted by Student ID Number. _ (Signature) PROBLEM 1 2 3 4 5 6 7 8 9 10 TOTAL POINTS 20 20 20 20 20 20 20 20 20 20 200 SCORE MANAGEMENT 1A
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Name: Student ID: Section: 2 Prof. Alan J. Laub Math 33A FINAL EXAMINATION Spring 2008 Instructions: June 9, 2008 (a) The exam is closed-book (except for one page of notes) and will last two and a half (2.5) hours. (b) Notation will conform as closely as
School: UCLA
Course: Math 32A
MATH 32A: SECOND PRACTICE MIDTERM EXAMINATION Summer 2008 1 1. (20 points) The C be a curve dened by the position function r(t) =< sin 2t, t, cos 2t >. (a) Calculate the equation of the Normal plane at the point (0, , 1). Its easier than you think.
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Management 1A Fall 2007 Danny S. Litt EXAM 1 Solutions I agree to have my grade posted by Student ID Number _ _ (Signature) (Student ID Number) Name: _ PROBLEM 1 2 3 4 5 6 7 8 TOTAL POINTS 30 30 20 30 20 20 20 30 200 SCORE MANAGEMENT 1A NAME: _
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A STUDY GUIDE FOR EXAM 1 This document is intended to help you study for the rst midterm. There are essentially 5 topics that will be on the exam, induction, sets, functions (including sequences and strings), relations (including equivalence relations) an
School: UCLA
This is the study guide for the second midterm of Math 61 in the winter quarter of 2014. The second midterm will cover the contents of Homeworks 4 through 6 except for the problems from Section 8.4. In particular it will cover Sections 6.2, 6.3, 6.7, 6.8,
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This is a review sheet for the nal exam of Math 61 in the winter quarter of 2014. The nal will be approximately 40% material from before the second midterm and 60% from after the second midterm. The sections comprising the 60% are Chapter 8 Sections 4-7 a
School: UCLA
Course: Introduction Of Complex Analysis
.~ 1. Suppose f is a holomorphic function defined on a region U which is simply connected(that is, which satisfies the Poincare Lemmal "p,q Theorem"). Show carefully using the PoiuG.are.-Lemrn,fthat there is a holomorphic function F with . F' =f everywhe
School: UCLA
Course: Stochastc Processes
Practice Midterm 2 solutions, Math 171, Spring 2015 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. If you have any questions raise your hand. The correct nal answer alone is not su
School: UCLA
Course: Stochastc Processes
Midterm 2, Math 171, Spring 2015 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. If you have any questions raise your hand. The correct nal answer alone is not sucient for full cred
School: UCLA
Course: Stochastc Processes
Practice Midterm 2, Math 171, Spring 2015 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. If you have any questions raise your hand. The correct nal answer alone is not sucient for
School: UCLA
Course: Stochastc Processes
Practice Midterm 1 solutions, Math 171, Spring 2015 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. If you have any questions raise your hand. The correct nal answer alone is not su
School: UCLA
Course: Stochastc Processes
Midterm 2, Math 171, Spring 2015 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. If you have any questions raise your hand. The correct nal answer alone is not sucient for full cred
School: UCLA
Course: Stochastc Processes
Midterm 1, Math 171 - Spring 2015 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. If you have any questions raise your hand. The correct nal answer alone is not sucient for full cre
School: UCLA
Course: Stochastc Processes
Practice Midterm 1, Math 171, Spring 2015 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. If you have any questions raise your hand. The correct nal answer alone is not sucient for
School: UCLA
Course: Stochastc Processes
Midterm 1, Math 171 - Spring 2015 Instructor: Toni Antunovi c c Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. If you have any questions raise your hand. The correct nal answer alone is not sucient for full cre
School: UCLA
Course: Stochastc Processes
Practice Final, Math 171 - Spring 2015 Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. Please raise your hand if you have questions at any time. The correct nal answer alone is not sucient for full credit - try
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Course: Stochastc Processes
Practice Final, Math 171 - Spring 2015 Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. Please raise your hand if you have questions at any time. The correct nal answer alone is not sucient for full credit - try
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Course: Multivariable Calculu
Pr 1 Pr 2 Pr 3 Pr 4 Pr 5 Pr 6 Pr 7 Pr 8 Pr 9 Pr 10 Pr 11 Total 10 10 10 10 10 10 10 10 10 10 5 100 Course 32 B UCLA Mathematics Department Instructor: Oleg Gleizer Summer 2014 Student: Midterm 2 Please print your name in the upper right corner of this pag
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Course: SYSTMS-DIFFNTL EQTN
"".'_"*r-.._.'. ".-u'. -.I - .' ' "fa-If- '_".-._'-.'31 '.. up I ac; 7 _____.__. __ q_ _-n I . 4%2rmcawiia «Eh: Qqsic .Pvffh-eipgg .9 sob-«Ind. .. o £02.0 reasowtgg , and we Sen/g. as an unclear? 18 + (PQFSI'EEWQ .MPz 3V5, Wh+ 0g 60
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MATH 31B, LECTURE 4 MIDTERM 2 FEBRUARY 27, 2012 Name: Solutions UID: TA: (circle one) Huiyi Hu Discussion meets: (circle one) Brent Nelson Tuesday Andrew Ruf Thursday Instructions: The exam is closed-book, closed-notes. Calculators are not permitted. Answ
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MATH 31B, LECTURE 4 MIDTERM 2 FEBRUARY 27, 2012 Name: UID: TA: (circle one) Huiyi Hu Discussion meets: (circle one) Brent Nelson Tuesday Andrew Ruf Thursday Instructions: The exam is closed-book, closed-notes. Calculators are not permitted. Answer each qu
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Course: Financial Mathematics
MATH 174E - 2 Financial Mathematics Midterm Examination Prof. Zachary Maddock November 12, 2014 First Name: Last Name: Bruin ID: Directions: This test is to be completed in approximately 50 minutes: 1. The use of notes, books or phones is not allowed, alt
School: UCLA
Course: Probability Theory
Practice midterm 1, Math 170a, Winter 2014 Printed name: Signed name: Student ID number: Instructions: Read problems very carefully. If you have any questions raise your hand. The correct nal answer alone is not sucient for full credit - try to explain
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 3 c c From the textbook solve the problems 29, 30, 31, 32 and 33 from the Chapter 4. Solve the problems 1, 2, 4, 5 and 6 from the Chapter 4 additional exercises at http:/www.athenasc.com
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi c c Homework 1 From the textbook solve the problems 1, 2, 3, 5, 6, 8, 11 and 14 at the end of the Chapter 4. And also the problems below: Problem 1. Give examples of (not independent) random variab
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Course: Mathemtcl Modeling
Math 142-2, Homework 1 Solutions April 7, 2014 Problem 34.4 Suppose the growth rate of a certain species is not constant, but depends in a known way on the temperature of its environment. If the temperature is known as a function of time, derive an expres
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Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 4 c c solutions From the textbook solve the problems 42, 43 b) and 44 b), c) from the Chapter 4. Solve the problems 26, 27 and 29 from the Chapter 4 and problem 1 from the Chapter 7 addi
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Course: Introduction Of Complex Analysis
EE101 Engineering Electromagnetics Winter 2013 2/14/13 Homework #5 Due: Thursday Feb 21 10:00 AM Hand in to the TA at beginning of class. No late homework is accepted (see grading policy posted on eeweb). If you cannot make it to class, you must slip the
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Math32a HW1 Due on Monday, Jan 14 All the numbered problems are from the textbook Multivariable Calculus by Rogawski (2nd edition). Note: if your textbook is Early Transcendentals by Rogawski (2nd edition), then all your chapters are shifted by 1 down. Th
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 3 c c From the textbook solve the problems 29, 30, 31, 32 and 33 from the Chapter 4. Solve the problems 1, 2, 4, 5 and 6 from the Chapter 4 additional exercises at http:/www.athenasc.com
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 6 c c Solve the problems 18 a) c) d) e) and 19 from the Chapter 7 additional exercises at http:/www.athenasc.com/prob-supp.html And also the problems below: Problem 1. Denote points P0 ,
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Course: Mathemtcl Modeling
Math 142 Homework 1 Solution 34.5 (a) If the growth rate is 0, the discrete model becomes Nm+1 Nm = tfm , And the solution is Nm = N0 + t(f0 + f1 + fm1 ), which is analogous to integration, since let t = mt, then t t(f0 + f1 + fm1 ) f (s)ds 0 for t small
School: UCLA
Course: Mathemtcl Modeling
Math 142 Homework 2 Solution 34.16 We will rstly proceed similarly as 34.14(c). We assume the theoretical growth has the form N0 eR0 t , and we hope to gure out which N0 and R0 t the data best. 34.14(b) suggests that N0 should be equal to the initial popu
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Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 5 c c From the textbook solve the problems 4 and 5 from the Chapter 5. Solve the problems 2, 4, 6, 7, 9 and 10 from the Chapter 7 additional exercises at http:/www.athenasc.com/prob-supp
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Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 2 c c From the textbook solve the problems 17, 18, 19, 22, 23 and 24 from the Chapter 4. Solve the problems 21, 22, 24, 30 from the Chapter 4 additional exercises at http:/www.athenasc.c
School: UCLA
Course: Introduction Of Complex Analysis
EE101 Engineering Electromagnetics Winter 2013 1/24/12 Homework #3 Due: Thursday Jan 31 10:00 AM Hand in to the TA at beginning of class. No late homework is accepted (see grading policy posted on eeweb). If you cannot make it to class, you must slip the
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Course: 245abc
Math 245A Homework 2 Brett Hemenway October 19, 2005 Real Analysis Gerald B. Folland Chapter 1. 13. Every -nite measure is seminite. Let be a -nite measure on X, M. Since is -nite, there exist a sequence of sets cfw_En in M, with (En ) < and En = X . n=1
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Course: Mathemtcl Modeling
Math 142 Homework 0 Solution 32.11 The easier way: (slightly unrigorous, but its ne for this class) Suppose the bank compounds the interest n times a year, and let t := 1/n. With the additional deposit (or withdrawl) D (t), the balance at time t + t is gi
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Homework 4 Solutions Math 3C Due: Friday Nov 2, 9 a.m. #1(a) Let X be a random variable that equals the number of defective items in the sample. When the sampling is done with replacement, X is binomially distributed with parameters n = 5 and p = 5/20 = 1
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Course: 245abc
Math 245A Homework 1 Brett Hemenway October 19, 2005 3. a. Let M be an innite -algebra on a set X Let Bx be the intersection of all E M with x E . Suppose y Bx , then By Bx because Bx is a set in M which contains y . But Bx By because if y E for any E M,
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Course: Mathemtcl Modeling
Math 142 Homework 1 Solution 32.3 (a) Use N (nt) to denote the population at time nt. Then for any n > 0, we have N (nt) = (1 + (b d)t)N (n 1)t) + 1000. (b) Given that N (0) = N0 , we hope to solve the equation above and get the general form for N (nt). T
School: UCLA
Course: Probability Theory
Probability Theory, Math 170b, Winter 2013, Toni Antunovi - Homework 4 c c From the textbook solve the problems 42, 43 b) and 44 b), c) from the Chapter 4. Solve the problems 26, 27 and 29 from the Chapter 4 and problem 1 from the Chapter 7 additional exe
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Course: Actuarial Math
MATH 115A - Assignment One - Solutions of Select Non-Graded Problems Paul Skoufranis October 3, 2011 1.2 Question 13) Let V denote the set of ordered pairs of real numbers. If (a1 , a2 ) and (b1 , b2 ) are elements of V and c R, dene (a1 , a2 ) + (b1 , b
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Course: Mathemtcl Modeling
Math 142-2, Homework 2 Solutions April 7, 2014 Problem 35.3 Consider a species in which both no individuals live to three years old and only one-year olds reproduce. (a) Show that b0 = 0, b2 = 0, d2 = 1 satisfy both conditions. All two year olds die befor
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Course: Real Analysis
Homework 8 Solutions Math 131A-3 1. Problems from Ross. (29.5) Suppose |f (x) f (y )| (x y )2 for all x, y in R. Then for any given a R, we )f )f have | f (xxa (a) | |x a|, so by the squeeze theorem, as x a, | f (xxa (a) | 0. Therefore f (a) = 0. Since a
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Course: Algebra
UCLA Mathematics 110A: selected solutions from homework #1 David Wihr Taylor July 2, 2010 Introduction When reading these solutions always keep in mind the common techniques being used. The point of homework, and subsequently these solutions, is to give y
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Course: Real Analysis
Math 131A Analysis Summer Session A Homework 3 Solutions n 1. Let (an ) be a bounded sequence and let (bn ) be a sequence such that lim bn = 0. Prove that lim an bn = 0. n Proof. Since (an ) is bounded, there exists M > 0 such that |an | < M for a
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1 1. Prove Proposition 3.1. Proposition 3.1 Let be a signed measure on . If is an increasing sequence in , then lim . If is a decreasing sequence in and is finite, then lim . Answer) Let be a signed measure on . a. If is an increasing sequence in
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Course: Linear Algebra
Ch. 1 Dept. of ECE, Faculty of Engineering University of Tehran Linear Algebra Homework # I Chapter 1: Vector Spaces Exercises to be handed: marked by *. Due date: Sunday Esfand 9th 1383. 1. Let V = cfw_ (a1 , a2) : a1 , a2 R . Define addition of elements
School: UCLA
Course: MULTIVARIABLE CALCULUS
This page intentionally left blank Students Solutions Manual to accompany Jon Rogawskis Single Variable CALCULUS SECOND EDITION BRIAN BRADIE Christopher Newport University ROGER LIPSETT W. H. FREEMAN AND COMPANY NEW YORK 2012 by W. H. Freeman and Company
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Mathematics 131A Assignment Page Homework 3 Exercise 1. Compute the sum of the series n=1 n2 1 . You may wish to factor the + 4n + 3 denominator. Exercise 2. Consider the series below and determine whether they are convergent or divergent. When possible,
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Mathematics 131A Assignment Page Homework 4 Exercise 1. Show that if f is dierentiable on (a, b), and if f = 0, then f is one-to-one on (a, b) and, in fact, a bijection. Exercise 2. Let f : (0, ) R be dened by f (x) = 1 . x+1 Prove using the denition of
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Mathematics 131A Assignment Page Homework 1 Exercise 1. If [P = Q] is a statement, then [Q = P ] is said to be its converse. Give an example of a true statement with a false converse and an example of a true statement with a true converse. Exercise 2. Pro
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Mathematics 131A Assignment Page Homework 2 Exercise 1. Using only the denition of convergence of a sequence, compute the limits of the following sequences: (a) an = 3n 3n + 1 4n 5n + 1 ; (b) an = ; (c) an = n ; (d) an = . n3 3n 1 2 n 3n 10 Exercise 2. Us
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Here are some solutions to the questions from homework 7 and 8 which are not in the book. Homework 7 #2. We call the square graph G = (V, E) where V = cfw_a, b, c, d and E = cfw_a, b, cfw_b, c, cfw_c, d, cfw_c, d. For part (a), a bijection from a set of s
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Be sure to write your name and section letter on your assignment! These problems are due on Friday January 10th at the beginning of lecture. Explain your answers. You should strive for both clarity and correctness. (1) Draw a circle. Place 3 dots along th
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Here are the solutions to the rst two problems on homework 2. (1) The best thing to do is to use induction. Let P (n) be the statement: In any line of n people which begins with a woman and ends with a man, there is a man standing immediately behind a wom
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This document contains solutions to the rst four problems of homework 1. (1) There was a little confusion on this problem about where to put the colors. The colors go on the arcs of the circle between the points. There are two cases. First suppose that yo
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Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 8 Due Friday May 22nd Solve the problems from Midterm 2 (you can nd it on CCLE week 8) and submit it as usual homework. 1
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 7 Due Friday May 15th Read section 1.10 in the book. Solve problems 1.70, 1.71 1.72, 1.73, 1.74 and 1.75 in the book. 1
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 5 Due Friday May 1st Read sections 1.5 and 1.6 in the book. Solve problems 1.13, 1.14, 1.30, 1.34, 1.41, 1.49, 1.50 and 1.51 in the book. Also solve the following. Problem 1. For the problem 1 from th
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 3 Due Friday April 24th Read section 1.4 in the book. Solve problems 1.9, 1.10, 1.11 and 1.12 on pages 76/77 in the book. Also solve the following. Problem 1. Consider the Markov chain on states cfw_1
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 5 Due Friday May 1st Read sections 1.5 and 1.6 in the book. Solve problems 1.13, 1.14, 1.30, 1.34, 1.41, 1.49, 1.50 and 1.51 in the book. Also solve the following. Problem 1. For the problem 1 from th
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 1 Due Friday April 10th Read section 1.1, 1.2 and 1.3 in the book. Solve problems 1, 2, 3, 5 and 7 on page 75 in the book and 45 from page 84. Also solve the following. Problem 1. Let X1 , X2 , . . .
School: UCLA
Course: Introduction Of Complex Analysis
' 3 ~ C.( _,~ s /YI'V~ Sv.ow ~4 ~(.a ~f'- r~ eHt) -:. G cfw_-t) (~'4~\-t.a-: ~M is :0. f: (~cr: -r cJ1 G/"G ,3 . 'l o. $~eM.~ C. ~t ~ &v-Q: ~., tt luL., ~ri~<- ~v~ F. ~evv.! tC.M Gi'f M ~t~) I ~. &~c:Jtt- c:~ ~ ,WUd~ 9> ~ fov ee-l ,:. 0 ~ ~c ~ ~ '~s . -
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 9 Due Friday May 29th Read section 4.1, 4.2 and 4.3 in the book. Solve problems 4.3, 4.4, 4.5 and 4.6 from the book, and the following problems. Problem 1. Consider a continuous time Markov chain on a
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 6 Due Friday May 8th Read sections 1.8 and 1.9 in the book. Solve problems 1.56, 1.57, 1.59, 1.60, 1.62, 1.64, 1.65 and 1.69 in the book. And problems below: Problem 1. There are n cells labeled with
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 6 Due Friday May 8th Read sections 1.8 and 1.9 in the book. Solve problems 1.56, 1.57, 1.59, 1.60, 1.62, 1.64, 1.65 and 1.69 in the book. And problems below: Problem 1. There are n cells labeled with
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 3 Due Friday April 17th Read section 1.3 in the book. Solve problems 1.6 and 1.8 on pages 75/76 in the book. Also solve the following. Problem 1. Consider independent tosses of a fair die. Let Zn cfw_
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 3 Due Friday April 17th Read section 1.3 in the book. Solve problems 1.6 and 1.8 on pages 75/76 in the book. Also solve the following. Problem 1. Consider independent tosses of a fair die. Let Zn cfw_
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 3 Due Friday April 24th Read section 1.4 in the book. Solve problems 1.9, 1.10, 1.11 and 1.12 on pages 76/77 in the book. Also solve the following. Problem 1. Consider the Markov chain on states cfw_1
School: UCLA
Course: Stochastc Processes
Stochastic Processes, Math 171, Spring 2015 - Homework 1 Due Friday April 10th Read section 1.1, 1.2 and 1.3 in the book. Solve problems 1, 2, 3, 5 and 7 on page 75 in the book and 45 from page 84. Also solve the following. Problem 1. Let X1 , X2 , . . .
School: UCLA
Course: Stochastc Processes
Math 171, Spring 2015 - Homework 1 Due Friday April 3rd Problem 1. Let X be a random variable with expectation 0 and variance 1. Compute E[X 2 + X]. Solution: Since E(X 2 ) = var(X) + (EX)2 = 1 + 02 = 1 we have E(X 2 + X) = E(X 2 ) + E(X) = 1 + 0 = 1. Pro
School: UCLA
Course: Stochastc Processes
Math 171, Spring 2015 - Homework 1 Due Friday April 3rd Problem 1. Let X be a random variable with expectation 0 and variance 1. Compute E[X 2 + X]. Problem 2. Let X be a Poisson random variable with parameter 1. Let Y be a Geometric random variable with
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Course: Math 31 B Lecture 4
Math 3C Hw # 5 due May 1 Name _ Section _ ID _ PRINT this page to use as a cover sheet. Staple your papers or use a paper clip. 1. You abet $4 , you roll a single die and you get back $1.10 times the number on the dice . What is the average win/loss for t
School: UCLA
Course: Math 31 B Lecture 4
Math 3C HW #1 due Monday April 6 at 8 am. NO late homework. Name _ Section _ UCLA ID # _ Print this page and attach it to your homework papers. Homework papers must be stapled. Do not turn in homework that is not legible or has scratch out marks on it. BE
School: UCLA
Course: SYSTMS-DIFFNTL EQTN
Contents Chapter 0. Before Calculus . 1 Chapter 1. Limits and Continuity . 39 Chapter 2. The Derivative .71 Chapter 3. Topics in Differentiation .109 Chapter 4. The Derivative in Graphing and Applications . 153 Chapter 5. Integration . 243 Chapter 6. Appl
School: UCLA
Course: SYSTMS-DIFFNTL EQTN
Math 170A: Homework #5 | Valore-Kemmerer, Duncan Problem 2.2 Problem 2.3 Problem 2.4 Problem 2.17 Supplementary Problem 2.2 Supplementary Problem 2.3 Page 1 Math 170A: Homework #5 | Valore-Kemmerer, Duncan Page 2 Math 170A: Homework #5 | Valore-Kemmerer,
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Course: Math 170
Probability Theory, Math 170b, Spring 2015, Toni Antunovi c c Homework 2 Due Friday, April 10th From the textbook solve the problems 1, 2, 3, 5, 6, 7 and 11 at the end of the Chapter 4. From the books supplementary problems, solve problem 19 in Chapter 3
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Course: Math 131a
Appendix on Set Notation Consider a set S. The notation x S means x is an element of S; we might also say x belongs to S or x is in S. The notation x S signies x is some element but x does not belong to S. By / T S we mean each element of T also belongs t
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Course: Discrete Math
HOMEWORK 3 (MATH 61, FALL 2015) Read: RJ, Sec. 6.2 and rst half of 6.7 (before identities). Solve: RJ, Sec. 6.2 Ex 6, 8, 29, 34, 35, 37, Sec. 6.7 Ex 2, 4, 5. I. Throughout the problem, assume n = 11. Compute the number of permutations a1 , . . . , an of c
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Math 172 B Class Project 1 Object: to download a specific mortality table from the Society of Actuaries website and utilize mortality rates to calculate life expectancies Steps: 1. Log onto www.soa.org 2. At the bottom of the opening page, select popular
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Course: Calculus
31B Notes Sudesh Kalyanswamy 1 Exponential Functions (7.1) The following theorem pretty much summarizes section 7.1. Theorem 1.1. Rules for exponentials: (1) Exponential Rules (Algebra): (a) ax ay = ax+y (b) ax ay = x y axy (c) (a ) = axy (2) Derivatives
School: UCLA
School: UCLA
School: UCLA
The Poisson distribution is a discrete distribution. It is often used as a model for the number of events (such as the number of telephone calls at a business, number of customers in waiting lines, number of defects in a given surface area, airplane arriv
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3C Notes Sudesh Kalyanswamy 1 Counting (12.1) 1.1 Guiding Questions for the Chapter Here are some questions for you to ask yourself as you read. If you can answer them all by the end, youre in pretty good shape as far as understanding the material. After
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3C Practice Problems for Midterm 1 Sudesh Kalyanswamy (1) Bills school schedule has four timeslots. Bill has 30 choices of classes for the rst timeslot, 20 for the second, 23 for the third, and 17 for the last. How many possible schedules are there? (2) C
School: UCLA
School: UCLA
Math 171 Spring 2013 Homework 8 (due Friday, June 7th at lecture time) (1) Read Sections 5.3 and 5.4. (2) Solve problems 2, 3, 4 and 6 from the end of chapter 5.
School: UCLA
School: UCLA
Course: INTEGRATION AND INFINITE SERIES
A dierential equation is an equation that relates the derivative of a function to that function (and possibly other functions). For example a dierential equation involving the function y (t) could look like dy (t) = ky (t) (1) dt for some constant k . Whe
School: UCLA
Course: Calculus
Answer Key B. Johnson Calculus AB Memory Quiz Important Relationships, Theorems, Rules, and Formulas Important Relationships 1. State the formal definition of derivative, include diagram. If y = f ( x ) then f ( x ) = lim h0 f ( x + h) f ( x) h 2. Where a
School: UCLA
Course: Linear Algebra
Math 33A, Sec. 2 Linear Algebra and Applications Spring 2012 Instructor: Professor Alan J. Laub Dept. of Mathematics / Electrical Engineering Math Sciences 7945 phone: 310-825-4245 e-mail: laub@ucla.edu Lecture: MWF 2:00 p.m. 2:50 p.m.; Rolfe 1200 Office
School: UCLA
Course: SYSTMS-DIFFNTL EQTN
Math 131 A/1: Analysis, UCLA, Spring 2015 Instructor name Dr. Roman Taranets, Department of Mathematics, UCLA E-mail: taranets @ math.ucla.edu Website: www.math.ucla.edu/~taranets Office Phone: (310) 825-4746 Office: MS 7360 Office Hours: MWF 9:00 am
School: UCLA
Course: SYSTMS-DIFFNTL EQTN
MATH 135-2 Instructor: Sungjin Kim, MS 6617A, E-mail: i707107@math.ucla.edu Meeting Time and Location: MWF 3:00 - 3:50 PM, Room: MS 5200 O ce Hours: MW 11:45 PM - 12:30 PM, Room: MS 6617A Textbook: G. Simmons, Dierential Equations (2nd) with Applications
School: UCLA
Course: Differential Equations
Math 33B, Differential Equations Lecture 1, Spring 2015 Instructor: Will Conley Email: wconley@ucla.edu Office: MS 6322 Office Hours: Tentatively Wednesdays 3:004:00 Thursdays 12:001:30 and 3:004:00, and by appointment Website: http:/www.math.ucla.edu/~wc
School: UCLA
Math 174E (Summer 2014) Mathematics of Finance Instructor: David W. Taylor Time/Location: MWR 11:00am-12:50pm in MS 5137. Text: Options, Futures, and Other Derivatives (8th edition) by John C. Hull. Instructor: David W. Taylor Oce Hours: TBA Email Address
School: UCLA
Math 174E, Lecture 1 (Winter 2014) Mathematics of Finance Instructor: David W. Taylor Time/Location: MWF 3:00pm-3:50pm in MS 5127. Text: Options, Futures, and Other Derivatives (8th edition) by John C. Hull. Instructor: David W. Taylor Oce Hours: Monday a
School: UCLA
Math 3B Integral calculus and differential equations Prof. M. Roper Young Hall CS 76, MWF 2-2.50pm. All inquiries about this class should be posted to the class Piazza page. The only emails that I will respond to are questions about how to login to Piazza
School: UCLA
Course: Calculus
Sample Syllabus Philosophical Analysis of Contemporary Moral Issues Winter 2015, MW 8-9:50 Instructor: Robert Hughes (hughes@humnet.ucla.edu) Instructor office hours: Dodd 378, M 11-12 and W 10-11 or by appointment TAs: Kelsey Merrill (kmerrill@humnet.ucl
School: UCLA
Course: Math 170
Probability Theory, Math 170A, Winter 2015 - Course Info Instructor: Tonci Antunovic, 6156 Math Sciences Building, tantunovic@math.ucla.edu, www.math.ucla.edu/~tantunovic Instructor Oce Hours: Monday 10-12am and Wednesday 9-10am in 6156 Math Sciences Buil
School: UCLA
Course: Math 1
Math1 Fall2012 Lecture1(8am),Lecture2(10am)andLecture3(1pm) Instructor Paige Greene E-Mail: paige@math.ucla.edu Office Number: MS 6617 B Office Hours: Mon and Wed (copy from me in class) Course Goals: The purpose of Math 1 is to give you a strong preparat
School: UCLA
Math33BDifferentialEquations Winter2015,lecture3 Time:MWF3:003:50p.m. Room:MS4000A Discussionsections: 3A T3:00P3:50PGEOLOGY6704 3B R3:00P3:50PGEOLOGY4645 Instructor:YuZhang Office:MS6617F Officehours:Monday2:003:00p.m. Wednesday4:006:00p.m. Email:yuzhang
School: UCLA
Math 3B Integral calculus and differential equations Prof. M. Roper Young Hall CS 76, MWF 2-2.50pm. All inquiries about this class should be posted to the class Piazza page. The only emails that I will respond to are questions about how to login to Piazza
School: UCLA
Course: Actuarial Math
Math 172A: Syllabus, Structure, Details and Policies (Fall 2014) Introduction to Financial Mathematics This course is designed to provide an understanding of basic concepts of actuarial/financial mathematics. The course touches most (but not all) syllabus
School: UCLA
Course: Abstract Algebra
Math 32B (Calculus of several variables), Section 2 Fall 2013 MWF 2:00-2:50 pm, 1178 Franz Hall UCLA Instructor: William Simmons, MS 6617A, simmons@math.ucla.edu. Oce Hours (held in MS 6617A): M: 8:00-8:55 am T: 10:30-11:30 am W: 3:30-4:30 pm Teaching Ass
School: UCLA
Math 115A, Linear Algebra, Lecture 6, Fall 2014 Exterior Course Website: http:/www.math.ucla.edu/heilman/115af14.html Prerequisite: MATH 33A, Linear algebra and applications. Course Content: Linear independence, bases, orthogonality, the Gram-Schmidt proc
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Math 32A, Calculus of Several Variables Lecture 1, Winter 2014 Instructor: Will Conley Email: wconley@ucla.edu Office: MS 6322 Office Hours: Tentatively Wednesdays 11:3012:30, Thursdays 1:302:30, and any other time by appointment. Website: http:/www.math.
School: UCLA
Math 33A, Section 2 Linear Algebra and Applications Winter 2014 Instructor: Professor Alan J. Laub Dept. of Mathematics / Electrical Engineering Math Sciences 7945 phone: 310-825-4245 e-mail: laub@ucla.edu Lecture: MWF 1:00 p.m. 1:50 p.m. Math Sciences 40
School: UCLA
Math1 Fall2012 Lecture1(8am),Lecture2(10am)andLecture3(1pm) Instructor Paige Greene E-Mail: paige@math.ucla.edu Office Number: MS 6617 B Office Hours: Mon and Wed (copy from me in class) Course Goals: The purpose of Math 1 is to give you a strong preparat
School: UCLA
Differential Equations MATH 33B-1 Instructor Details: Lecture 1: Instructor: Office: Office hours: MWF 12PM-12:50PM in MOORE 100 Prof. Zachary Maddock MS 6236 (MS := Mathematical Sciences) Mondays 1:30PM-2:30PM Wednesdays 9:50AM-10:50AM, 1:30PM-2:30PM Tea
School: UCLA
Course: Linear Algebra
Course information and Policy, v. of Oct.1st, 2013 Marc-Hubert NICOLE Linear Algebra with Applications Math 33A-1, Lecture 1, Fall 2013. U.C.L.A. -Instructor Marc-Hubert NICOLE Lectures: MWF 8:00-8:50 AM in Rolfe 1200. Ofce: MS 5230 (see Ofce Hours belo
School: UCLA
Course: Linear Algebra
Winter 2011, UCLA Department of Economics Economics 106G: Introduction to Game Theory Instructor: Ichiro Obara Bunche 9381 E-mail: iobara@econ.ucla.edu Web: http:/www.econ.ucla.edu/iobara Office Hour: Tuesday 1:00pm - 2:30pm or by appointment. Time and Lo
School: UCLA
Course: Linear Algebra
Math 115A Fall 2012 Professor: David Gieseker Oce: Math Sciences 5636. Phone: 206-6321, email: dag at math ucla edu Oce Hours: M, W, F 9:30-10, 11-11:30. M,W 2-2:30 and by appointment. Text: Linear Algebra, Friedberg, Insel, Spence. Material to be covered
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S YLLABUS : P HYSICS 1B, L ECTURE 1, W INTER 2012 I NSTRUCTOR : Prof. Troy Carter 4-909 PAB (310) 825-4770 tcarter@physics.ucla.edu O FFICE H OURS : M 10-11AM, T 1PM-2PM, F 1-2PM, other times by appointment C OURSE A DMINISTRATOR : Elaine Dolalas (handles
School: UCLA
Course: Introduction Of Complex Analysis
Math 132: Complex Analysis for Applications INSTRUCTOR: Kefeng Liu TIME and LOCATION: MWF 9:00-9:50AM, MS5117. OFFICE HOURS: TT 9:00-10:00AM in MS 6330 (Or by appointment) SYLLABUS: Official Syllabus Text: Complex Analysis by Tom Gamelin TA: Wenjian Liu,
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Math 3C, Probability for Life Sciences Students, Lecture 2, Spring 2012 Instructor: Thomas Sinclair E-mail: thomas.sinclair@math.ucla.edu Oce: Math Sciences (MS) 7304 Oce Hours: M 3:004:30, W 11:0012:30 TAs: 2a,b Theodore Gast Oce: MS 2961 Oce Hours: TBA
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Mathematics 31B: Integration and Innite Series. Fall 2012 Instructor: David Weisbart Email: dweisbar@math.ucla.edu Textbook: J. Rogawski, Single Variable Calculus, 2nd Ed., W.H. Freeman & Co. 31B Teaching Statement: Along with 31A, this course is the foun
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Course: Linear Algebra
Physiological Science 5 Issues in Human Physiology: Diet and Exercise Winter 2012 Instructor: Joseph Esdin, Ph.D. Office Hours: Mon 12:30-1:20 pm & Wed 10:30-11:20 am Office: 3326 Life Sciences Building Phone: (310) 825-4118 Email: yezzeddi@ucla.edu TA: D
School: UCLA
Course: Linear Algebra
Mathematics 33B: Dierential Equations. Winter 2012 Instructor: David Weisbart Email: dweisbar@math.ucla.edu Textbook: Polking, Boggess, Arnold, Dierential Equations, 2nd Ed., Pearson. 33B Teaching Statement: Since the time of Newton, the language of diere
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ULE ZLER, UCLA ECONOMICS DEPARTMENT BUCHE HALL 9361 OZLER@ECON.UCLA.EDU OFFICE HOURS: TUE & THR 1:00-1:45 AND BY APPOINTMENT ONLY FALL 2011 ECONOMICS 121- INTERNATIONAL TRADE THEORY Course Description In this course we will study alternative models of int
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Course: Math 26
Math 26B Section 2 Calculus II for the Social and Life Sciences Fall 2012 Instructor: Jill Macari Office: Brighton Hall 121 Phone: 278-7074 Email: jmacari@csus.edu Office Hours: Monday, Tuesday, and Wednesday 10:30 am 11:30 am; Thursday 12:30 pm 1:30 pm a
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Math 131A Course Outline Spring 2011 Text: Apostol, Calculus, Volume I, 2nd ed. Instructor: Betsy Stovall 1. Introduction. Crash review of basic propositional logic and set notation. (Chapter I.2) On your own: Read I.12 with an emphasis on I.2. You wil
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Course: 245abc
1. AssignmentdueSeptember7:ChapterI,4(ignorethe hypothesisthatKnormalizesH),5,6,7,8,9.In Problem8,thereisapairofmisprints:astheproblemis written,therearethreeunionsigns,wheretheindices arerespectivelyc,x_candx_c.Thefirstunionshould beoverelementsx_c;thes
School: UCLA
Course: Mathematics-finance
Course Syllabus Math 181: THE MATHEMATICS OF FINANCE Fall 2001 1 Background in Finance and Probability 1. Introduction and Course Description 2. Review of probability 3. Discrete Random Walks 4. Random walks with Gaussian increments 5. Equity model
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Course: Prob Life Sci Stdt
Math 3C (Spring 2008) Probability for Life Sciences Students Instructor: Roberto Schonmann www.math.ucla.edu/rhs Time/Place: Lecture 1: MWF 9:00-9:50 in MS 4000A. Lecture 2: MWF 10:00-10:50 in MS 4000A. Text: Calculus for Biology and Medicine (second