Online study resources available anywhere, at any time
High-quality Study Documents, expert Tutors and Flashcards
Everything you need to learn more effectively and succeed
We are not endorsed by this school |
- Course Hero has verified this tag with the official school catalog
We are sorry, there are no listings for the current search parameters.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
We don't have any study resources available yet.
School: Berkeley
Course: STAT 21
Quiz 1 Statistics 21 Spring 2010 Ibser 1. A large class takes a test, and the table shows their scores. For all parts of this problem, assume that the scores are continuous and that they are evenly distributed within each separate class interval. The maxi
School: Berkeley
Course: Intro To Probability And Statistics
Statistics 20: Summer Session 2007 Quiz n. 1 Friday July 6, 2007 Full Name (Please print): ID: Lab: YOU MUST SHOW WORK TO RECEIVE ANY CREDIT 1. The British government conducts regular surveys of household spending. The average weekly household spending on
School: Berkeley
STAT516 Solution to Homework 2 1.4.5: a) Let U1=(urn 1 chosen), U2=(urn 2 chosen), B=(black ball chosen), W=(White ball chosen). 2/5 B 1/2 U1 3/5 4/7 W B 1/2 U2 3/7 W b) P(U1)=1/2=P(U2); P(W|U1)=3/5; P(B|U1)=2/5; P(W|U2)=3/7; P(B|U2)=4/7 c) P(B)=P(B|U1)P(
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Problem Set 5 Fall 2011 Issued: Thursday, November 10, 2011 Due: Wednesday, November 30, 2011 Problem 5.1 Conv
School: Berkeley
Course: 135
Stat 135, Fall 2011 A. Adhikari HOMEWORK 5 (due Friday 10/7) 1. 9.11. Use R to do the plots accurately. In each case, say what the limiting power is as approaches 0. 2. 9.12. 3. 9.13. In c, use R to nd the critical values x0 and x1 . Turn the page for d.
School: Berkeley
Lab 2 Solutions Stat 135 Tessa Childers-Day March 3, 2011 1 Chapter 8, Problem 43 Please note that I was very specific of the format of the report. I posted an example report, and noted several times that the code was to be printed separately from the ans
School: Berkeley
School: Berkeley
School: Berkeley
Review problems for MT 1 S.M. Stoyanov 1. Given below is a distribution table for the 1993 salaries (in thousands of dollars) of the top 60 small companies (according to Forbes magazine). Each interval contains the right endpoint and not the left. You can
School: Berkeley
Review problems for MT 1 (with solutions) S.M. Stoyanov 1. Given below is a distribution table for the 1993 salaries (in thousands of dollars) of the top 60 small companies (according to Forbes magazine). Each interval contains the right endpoint and not
School: Berkeley
Introductory Probability and Sta1s1cs for Business Stat 21 Fall 2012 Shobhana M. Stoyanov 9/24/2013 Chapters 13,14,15: Probability Also using notes, and S1ciGui Chapter 13: Chance How would you dene chance?
School: Berkeley
Introductory Probability and Sta1s1cs for Business Stat 21 Fall 2013 Shobhana Stoyanov Lecture 6 9/17/2013 Regression: Chapters 10, 11, 12 Correla1on Cau1ons Correla1on only tells you about a linear
School: Berkeley
Psych 133 Allison Harvey Section Friday 1 2 pm Hyunjoong Joo 23208055 Reaction Paper of Sleep and youth suicidal behavior: a neglected eld Sleep undergoes continuous changes during puberty and additionally, suicide risks begin to escalate during this peri
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
v ~ ~- Jk_ Yu~ ~-+- l J& c+-e ~ & ~-~-~ sh(/cfw_1 ~ ~/s /U~ (l[J_;_I_o_ _ ;/lk _ ~1J~- I/J10d? /178 /() if_ ( ;1 _ :-.mJe_- _ )_fL~ft-r-~fce ~-('~ q~- - - - 01~ jv;/ how O!c-1-utA (c-r~Aud . -+-gj_ 1/t_Q - - - - tJ t1rlf;7; -Jt&z ;v; -~- - - - - - - - -
School: Berkeley
Course: Game Theory
Game Theory, Alive Anna R. Karlin and Yuval Peres Draft January 20, 2013 Please send comments and corrections to karlin@cs.washington.edu and peres@microsoft.com i We are grateful to Alan Hammond, Yun Long, Gbor Pete, and Peter a Ralph for scribing early
School: Berkeley
School: Berkeley
AverageSoFar 58.33 58.00 57.67 57.33 57.33 57.33 57.00 56.83 56.67 56.67 56.50 56.33 56.33 56.33 56.17 56.00 56.00 55.67 55.67 55.50 55.33 55.33 55.33 55.33 55.17 55.00 54.83 54.67 54.50 54.33 54.33 54.00 54.00 53.83 53.83 53.67 53.67 53.50 53.33 53.33 53
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 24: 2 Testing Tessa L. Childers-Day UC Berkeley 5 August 2014 Recap Test for Distribution Test for Independence Recap: Hypothesis Testing Steps in Hypothesis Testing: 1 State the hypotheses Null: The di
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 23: Two Sample Testing Tessa L. Childers-Day UC Berkeley 4 August 2014 Recap Surveys Experiments Recap: Hypothesis Testing Steps in Hypothesis Testing: 1 State the hypotheses Null: The dierence between
School: Berkeley
Course: STAT 21
Quiz 1 Statistics 21 Spring 2010 Ibser 1. A large class takes a test, and the table shows their scores. For all parts of this problem, assume that the scores are continuous and that they are evenly distributed within each separate class interval. The maxi
School: Berkeley
Course: Intro To Probability And Statistics
Statistics 20: Summer Session 2007 Quiz n. 1 Friday July 6, 2007 Full Name (Please print): ID: Lab: YOU MUST SHOW WORK TO RECEIVE ANY CREDIT 1. The British government conducts regular surveys of household spending. The average weekly household spending on
School: Berkeley
UGBA 103, Midterm Exam: March 05, 2012 Name: ID: Section: The answers on this midterm are entirely my own work. I neither gave nor received any aid while taking this midterm. _ Signature Please remember to write your name legibly on every page. The maximu
School: Berkeley
Course: Probability
Statistics 2 Problems from past nal exams 1. (5 points) The paragraph below is taken from an article in the San Francisco Chronicle of Tuesday, March 21, 1995. The person quoted in the article is Patrick Portway, executive director of the United States Di
School: Berkeley
STAT 20 - Fall 2011 - Practice Midterm 1 Most explanations require just a sentence or two. On calculations, show your work and work through to a numerical answers, upto at least 2 decimal places. 1. Below are the statistics of 3 lists of numbers. The aver
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Practice Midterm 2 1. We surveyed 100 women about their weights and heights, and got the following results; average height = 64 inches, average weight = 140 pounds, SD = 4 inches SD = 15 pounds The correlation coecient r between the heights and weights wa
School: Berkeley
STAT516 Solution to Homework 2 1.4.5: a) Let U1=(urn 1 chosen), U2=(urn 2 chosen), B=(black ball chosen), W=(White ball chosen). 2/5 B 1/2 U1 3/5 4/7 W B 1/2 U2 3/7 W b) P(U1)=1/2=P(U2); P(W|U1)=3/5; P(B|U1)=2/5; P(W|U2)=3/7; P(B|U2)=4/7 c) P(B)=P(B|U1)P(
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Problem Set 5 Fall 2011 Issued: Thursday, November 10, 2011 Due: Wednesday, November 30, 2011 Problem 5.1 Conv
School: Berkeley
Course: 135
Stat 135, Fall 2011 A. Adhikari HOMEWORK 5 (due Friday 10/7) 1. 9.11. Use R to do the plots accurately. In each case, say what the limiting power is as approaches 0. 2. 9.12. 3. 9.13. In c, use R to nd the critical values x0 and x1 . Turn the page for d.
School: Berkeley
Course: 135
Stat 135, Fall 2011 A. Adhikari HOMEWORK 4 (due Friday 9/30) 1. 8.20. Use R to do this one accurately. Be careful about constants when youre working out the distribution of 2 . 2. 8.32. You dont have to do all six intervals in parts (b) and (c); just do t
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Problem Set 1 Fall 2011 Issued: Thurs, September 8, 2011 Due: Monday, September 19, 2011 Reading: For this pro
School: Berkeley
Statistics 20: Quiz 4 Solutions 1. A team of doctors want to estimate the life expectancy of students afflicted with the rare genetic disease statinotisticitis; however, only 15 known cases have ever been diagnosed. The sample reported a mean lifespa
School: Berkeley
Stat 215B (Spring 2005): Lab 3 GSI: Victor Panaretos victor@stat.berkeley.edu Due March 8 at the Lab Section Part 1 : Simultaneous Inference In this section we revisit the data from the previous lab. Recall that the scenario involved the study of li
School: Berkeley
1 1 2 5 3&4 1 2&5 3 4 135 1 4 2 3&5 1 4&5 2 3 154 1&2 4&5 1&2&4 5 3 1&3 4 2&5 1&3&5 4 2 1&4 5 2&3 12 1254 1 2&5 3&4 1352 1425 1 4&5 2&3 1542 1&2 4&5 3 1&2&4&5 1&3 4 5 1&4 1&4 5 3 123 12543 1 2&5 4 13524 14253 1 4&5 3 15423 1&2 5 1&2&4&5 3 1&3 4 5 2 1&4 2
School: Berkeley
Course: Concepts Of Probability
Statistics 134, Section 2, Spring 2010 Instructor: Hank Ibser Lectures: TTh 11-12:30 in 60 Evans. Oce Hours: TTh 9:30-10:30 and 3:40-4:30, in 349 Evans Hall. Other times/places by appt. Oce Phone: 642-7495 Email: hank@stat.berkeley.edu Text: Probability b
School: Berkeley
Course: Introductory Probability And Statistics For Busines
UNIVERSITY OF CALIFORNIA Department of Economics Econ 100B Course Outline Spring 2012 Economics 100B Economic Analysis: Macroeconomics Professor Steven A. Wood Administrative Detail: Class Sessions: Tuesdays and Thursdays, 3:30 p.m. 5:00 p.m., 2050 Valley
School: Berkeley
Course: Introductory Probability And Statistics For Busines
Statistics 21, Section 1, Spring 2012 Instructor: Hank Ibser Lectures: MWF 9-10, 155 Dwinelle Email: hank@stat.berkeley.edu Office Hours: MW 10:10-11, 1:10-2, in 349 Evans Hall. Text: Statistics, 4rd ed. by Freedman, Pisani, Purves, Well cover most of cha
School: Berkeley
Course: Introductory Probability And Statistics For Busines
Schedule for Stat 21, Fall 2013 Note: Chapter readings are from FPP, and SG refers to Professor Philip Starks free online text SticiGui. notes by RP indicates Professor Roger Purves notes on chance variables, which will be posted on Canvas later. Week 1 (
School: Berkeley
Course: Introductory Probability And Statistics For Busines
STAT 21 Syllabus Course Information: Instructor: Shobhana Murali Stoyanov, shobhana@stat.berkeley.edu Class time: TuTh 2-3:30P, F295 Haas Office hours: W: 11-1P & by appointment, 325 Evans Text: Statistics, 4th ed., by Freedman, Pisani, and Purves. Supple
School: Berkeley
Statistics 21, Section 1, Spring 2010 Instructor: Hank Ibser Lectures: TTh 2-3:30pm, 2050 VLSB Email: hank@stat.berkeley.edu Oce Phone: 642-7495 Oce Hours: TuTh 9:30-10:30, 3:40-4:30, in 349 Evans Hall. Other times/places by appointment. Text: Statistics,
School: Berkeley
Course: STAT 21
Quiz 1 Statistics 21 Spring 2010 Ibser 1. A large class takes a test, and the table shows their scores. For all parts of this problem, assume that the scores are continuous and that they are evenly distributed within each separate class interval. The maxi
School: Berkeley
Course: Intro To Probability And Statistics
Statistics 20: Summer Session 2007 Quiz n. 1 Friday July 6, 2007 Full Name (Please print): ID: Lab: YOU MUST SHOW WORK TO RECEIVE ANY CREDIT 1. The British government conducts regular surveys of household spending. The average weekly household spending on
School: Berkeley
STAT516 Solution to Homework 2 1.4.5: a) Let U1=(urn 1 chosen), U2=(urn 2 chosen), B=(black ball chosen), W=(White ball chosen). 2/5 B 1/2 U1 3/5 4/7 W B 1/2 U2 3/7 W b) P(U1)=1/2=P(U2); P(W|U1)=3/5; P(B|U1)=2/5; P(W|U2)=3/7; P(B|U2)=4/7 c) P(B)=P(B|U1)P(
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Problem Set 5 Fall 2011 Issued: Thursday, November 10, 2011 Due: Wednesday, November 30, 2011 Problem 5.1 Conv
School: Berkeley
Course: 135
Stat 135, Fall 2011 A. Adhikari HOMEWORK 5 (due Friday 10/7) 1. 9.11. Use R to do the plots accurately. In each case, say what the limiting power is as approaches 0. 2. 9.12. 3. 9.13. In c, use R to nd the critical values x0 and x1 . Turn the page for d.
School: Berkeley
Lab 2 Solutions Stat 135 Tessa Childers-Day March 3, 2011 1 Chapter 8, Problem 43 Please note that I was very specific of the format of the report. I posted an example report, and noted several times that the code was to be printed separately from the ans
School: Berkeley
Course: 135
Stat 135, Fall 2011 A. Adhikari HOMEWORK 4 (due Friday 9/30) 1. 8.20. Use R to do this one accurately. Be careful about constants when youre working out the distribution of 2 . 2. 8.32. You dont have to do all six intervals in parts (b) and (c); just do t
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Problem Set 1 Fall 2011 Issued: Thurs, September 8, 2011 Due: Monday, September 19, 2011 Reading: For this pro
School: Berkeley
Statistics 20: Quiz 4 Solutions 1. A team of doctors want to estimate the life expectancy of students afflicted with the rare genetic disease statinotisticitis; however, only 15 known cases have ever been diagnosed. The sample reported a mean lifespa
School: Berkeley
Math 361/Stat 351 X1 Homework 10 Solutions Spring 2003 Graded problems: 1(d), 3(c), 4(b), 7 Problem 1. [4.2.4] Suppose component lifetimes are exponentially distributed with mean 10 hours. Find (a) the probability that a component survives 20 hou
School: Berkeley
UGBA 103, Midterm Exam: March 05, 2012 Name: ID: Section: The answers on this midterm are entirely my own work. I neither gave nor received any aid while taking this midterm. _ Signature Please remember to write your name legibly on every page. The maximu
School: Berkeley
Statistics 20: Quiz 1 Solutions Speed (mph) 0-10 10-20 20-40 40-80 80-95 Percentage of Total Cars 20 10 40 20 10 The above table depicts data collected in a (hypothetical) survey studying the distribution of traffic speed on the Bay Bridge. Each gro
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Problem Set 3 Fall 2011 Issued: Monday, October 10, 2011 Due: Monday, October 24, 2011 Reading: For this probl
School: Berkeley
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Solutions to Problem Set 3 Fall 2011 Issued: Monday, October 10, 2011 Due: Monday, October 24, 2011 Reading: F
School: Berkeley
Course: 135
Stat 135, Fall 2011 HOMEWORK 8 due WEDNESDAY 11/9 at the beginning of lecture Friday 11/11 is a holiday, so this is a very short homework due two days earlier at the start of lecture. Grading: A (4 points) for all three problems done well, B (2 points) fo
School: Berkeley
Course: Probability
Homework # 2 Statistics 134, Pitman , Spring 2009 2.1.2 P (2 boys and 2 girls) = 4 (1/2)4 = 6/24 = 0.375 < 0.5. So families with dierent 2 numbers of boys and girls are more likely than those having an equal number of boys and girls, and the relative freq
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Solutions to Problem Set 1 Fall 2011 Issued: Thurs, September 8, 2011 Due: Monday, September 19, 2011 Reading:
School: Berkeley
Course: 135
Stat 135, Fall 2011 HOMEWORK 1 (due Friday 9/9) 1a) Let x1 , x2 , . . . , xn be a list of numbers with mean and SD . Show that 2 = 1 n n x2 2 i i=1 b) A class has two sections. Students in Section 1 have an average score of 75 with an SD of 8. Students in
School: Berkeley
Course: Concepts Of Probability
Statistics 134, Section 2, Spring 2010 Instructor: Hank Ibser Lectures: TTh 11-12:30 in 60 Evans. Oce Hours: TTh 9:30-10:30 and 3:40-4:30, in 349 Evans Hall. Other times/places by appt. Oce Phone: 642-7495 Email: hank@stat.berkeley.edu Text: Probability b
School: Berkeley
Course: Introductory Probability And Statistics For Busines
- Home | Text Table of Contents | Assignments | Calculator | Tools | Review | Glossary | Bibliography | System Requirements | Author's Homepage Chapter 21 Testing Equality of Two Percentages Chapter 19, "Hypothesis Testing: Does Chance Explain the Results
School: Berkeley
Course: Probability
Homework 8 Problems Statistics 134, Pitman , Fall 2012 4.2.4 Suppose component lifetimes are exponentially distributed with mean 10 hours. Find: 1. the probability that a component survives 20 hours; 2. the median component lifetime; 3. the SD of componen
School: Berkeley
Math 4653: Elementary Probability: Spring 2007 Homework #6. Problems and Solutions 1. Sec. 4.2: #6: A Geiger counter is recording background radiation at an average rate of one hit per minute. Let T3 be the time in minutes when the third hit occurs after
School: Berkeley
Math 4653: Elementary Probability: Spring 2007 Homework #1. Problems and Solutions 1. Appendix 1 (vi): Prove that 2n n n = k=0 n k n n-k n = k=0 n k 2 . Solution. The left side is the number of all subsets of the set cfw_1, 2, . . . , n-1, n, n+1, . . . ,
School: Berkeley
Math 4653: Elementary Probability: Spring 2007 Homework #5. Problems and Solutions 1. Sec. 3.5: #2: How many raisins must cookies contain on average for the chance of a cookie containing at least one raisin to be at least 99%? Solution. Let X be the numbe
School: Berkeley
Math 4653: Elementary Probability: Spring 2007 Homework #4. Problems and Solutions 1. Sec. 3.1: #8a): A hand of five cards contains two aces and three kings. The five cards are shuffled and dealt one by one, until an ace appears. Display in a table the di
School: Berkeley
Course: Introductory Probability And Statistics For Busines
UNIVERSITY OF CALIFORNIA Department of Economics Econ 100B Course Outline Spring 2012 Economics 100B Economic Analysis: Macroeconomics Professor Steven A. Wood Administrative Detail: Class Sessions: Tuesdays and Thursdays, 3:30 p.m. 5:00 p.m., 2050 Valley
School: Berkeley
Math 361 X1 Homework 4 Solutions Spring 2003 Graded problems: 1(b)(d); 3; 5; 6(a); As usual, you have to solve the problems rigorously, using the methods introduced in class. An answer alone does not count. The problems in this assignment are inte
School: Berkeley
Math 361 X1 Homework 6 Solutions Spring 2003 Graded problems: 2(a);4(a)(b);5(b);6(iii); each worth 3 pts., maximal score is 12 pts. Problem 1. [3.1:4] Let X1 and X2 be the numbers obtained on two rolls of a fair die. Let Y1 = max(X1 , X2 ) and Y2
School: Berkeley
Math 361 X1 Homework 9 Solutions Spring 2003 Graded problems: 1(a), 2, 4(b), 5(b) (3 points each - 12 points maximal); 7 (Bonus problem): up to 2 additional points Problem 1. [4.R:25, variant] Suppose U is distributed uniformly on the interval (0
School: Berkeley
Course: Probability
Statistics 2 Problems from past nal exams 1. (5 points) The paragraph below is taken from an article in the San Francisco Chronicle of Tuesday, March 21, 1995. The person quoted in the article is Patrick Portway, executive director of the United States Di
School: Berkeley
Math 4653: Elementary Probability: Spring 2007 Homework #3. Problems and Solutions 1. Sec. 2.4: #2: Find Poisson approximations to the probabilities of the following events in 500 independent trials with probability 0.02 of success on each trial: a) 1 suc
School: Berkeley
STAT 20 - Fall 2011 - Practice Midterm 1 Most explanations require just a sentence or two. On calculations, show your work and work through to a numerical answers, upto at least 2 decimal places. 1. Below are the statistics of 3 lists of numbers. The aver
School: Berkeley
Course: Introductory Probability And Statistics For Busines
Statistics 21, Section 1, Spring 2012 Instructor: Hank Ibser Lectures: MWF 9-10, 155 Dwinelle Email: hank@stat.berkeley.edu Office Hours: MW 10:10-11, 1:10-2, in 349 Evans Hall. Text: Statistics, 4rd ed. by Freedman, Pisani, Purves, Well cover most of cha
School: Berkeley
Math 361 X1 Homework 8 Solutions Spring 2003 Graded problems: 1, 4(b), 5, 6; 3 points each, 12 points total Problem 1. In a certain math class each homework problem is scored on a 0 3 point scale. A lazy grader decides to grade these problems by
School: Berkeley
Math 4653: Elementary Probability: Spring 2007 Homework #7. Problems and Solutions 1. Ch. 4, Review: #21: Suppose R1 and R2 are two independent random variables with the 1 same density function f (x) = x exp(- 2 x2 ) for x 0. Find a) the density of Y = mi
School: Berkeley
Math 361 X1 Homework 1 Solutions Spring 2003 Graded problems: 1; 2(b);3;5; each worth 3 pts., maximal score is 12 pts. Problem 1. A coin is tossed repeatedly. What is the probability that the second head appears at the 5th toss? (Hint: Since only
School: Berkeley
Math 4653: Elementary Probability: Spring 2007 Homework #2. Problems and Solutions (corrected) 1. Sec. 1.5: #2: Polyas urn scheme. An urn contains 4 white balls and 6 black balls. A ball is chosen at random, and its color noted. The ball is then replaced,
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
v ~ ~- Jk_ Yu~ ~-+- l J& c+-e ~ & ~-~-~ sh(/cfw_1 ~ ~/s /U~ (l[J_;_I_o_ _ ;/lk _ ~1J~- I/J10d? /178 /() if_ ( ;1 _ :-.mJe_- _ )_fL~ft-r-~fce ~-('~ q~- - - - 01~ jv;/ how O!c-1-utA (c-r~Aud . -+-gj_ 1/t_Q - - - - tJ t1rlf;7; -Jt&z ;v; -~- - - - - - - - -
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Practice Midterm 2 1. We surveyed 100 women about their weights and heights, and got the following results; average height = 64 inches, average weight = 140 pounds, SD = 4 inches SD = 15 pounds The correlation coecient r between the heights and weights wa
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
MIDTERM 2 04/16/2014 Olena Blumberg Name: GSI and Section #: Show your work for all the problems. Good luck! 1. We surveyed 100 men about their weights and heights, and got the following results: average height = 69 inches, average weight = 170 pounds, SD
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
FINAL EXAM 05/14/2014 Olena Blumberg Name: GSI and Section #: Show your work for all the problems. Good luck! 1. In a certain school district, about 7% of the students are homeschooled, and the remaining 93% go to conventional schools. The average SAT sco
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
FINAL EXAM 05/14/2014 Olena Blumberg Name: GSI and Section #: Show your work for all the problems. Good luck! 1. [5 pts] A researcher is interested in whether more sleep boosts the immune system. So she calls a random sample of 400 people and asks them ho
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
FINAL EXAM 05/14/2014 Olena Blumberg Name: GSI and Section #: Show your work for all the problems. Good luck! 1. In a certain school district, about 7% of the students are homeschooled, and the remaining 93% go to conventional schools. The average SAT sco
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Practice Midterm 1 1. According to an observational study done at Kaiser Permanente in Walnut Creek, California, users of oral contraceptives have a higher rate of cervical cancer than non-suers, even after adjusting for age, educations, marital status, r
School: Berkeley
1 1 2 5 3&4 1 2&5 3 4 135 1 4 2 3&5 1 4&5 2 3 154 1&2 4&5 1&2&4 5 3 1&3 4 2&5 1&3&5 4 2 1&4 5 2&3 12 1254 1 2&5 3&4 1352 1425 1 4&5 2&3 1542 1&2 4&5 3 1&2&4&5 1&3 4 5 1&4 1&4 5 3 123 12543 1 2&5 4 13524 14253 1 4&5 3 15423 1&2 5 1&2&4&5 3 1&3 4 5 2 1&4 2
School: Berkeley
Course: Game Theory
Game Theory, Alive Anna R. Karlin and Yuval Peres Draft January 20, 2013 Please send comments and corrections to karlin@cs.washington.edu and peres@microsoft.com i We are grateful to Alan Hammond, Yun Long, Gbor Pete, and Peter a Ralph for scribing early
School: Berkeley
School: Berkeley
School: Berkeley
School: Berkeley
AverageSoFar 58.33 58.00 57.67 57.33 57.33 57.33 57.00 56.83 56.67 56.67 56.50 56.33 56.33 56.33 56.17 56.00 56.00 55.67 55.67 55.50 55.33 55.33 55.33 55.33 55.17 55.00 54.83 54.67 54.50 54.33 54.33 54.00 54.00 53.83 53.83 53.67 53.67 53.50 53.33 53.33 53
School: Berkeley
STATISTICS 21 Fall 2012 S. M. Stoyanov MIDTERM 1 Score:[ /60] Please show ALL WORK AND REASONING for ALL the problems.You may NOT use a programmable calculator for this quiz. Do NOT ROUND the numbers in the middle of a problem. In general, unless asked to
School: Berkeley
STATISTICS 21 Fall 2012 S. M. Stoyanov MIDTERM 2 Score:[ Name: /60] SID: Section: Please circle your sections GSI: Tina Ansari Nathan Cheung Andrew Kwong Nazret Weldeghiorgis Susannah Lee Arie Wong Please show ALL WORK AND REASONING for ALL the problems.Y
School: Berkeley
Statistics 21 Fall 2012 Shobhana M. Stoyanov Midterm 2 Score:[ Name: /60] SID: Section: Please circle your sections GSI: Tina Ansari Nathan Cheung Andrew Kwong Nazret Weldeghiorgis Susannah Lee Arie Wong Please show ALL WORK AND REASONING for ALL the prob
School: Berkeley
Statistics 21 Fall 2012 Shobhana M. Stoyanov Midterm 1: Answers Score:[ /60] Please show ALL WORK AND REASONING for ALL the problems.You may NOT use a programmable calculator for this quiz. Do NOT ROUND the numbers in the middle of a problem. In general,
School: Berkeley
STATISTICS 21 FALL 2013 S. M. Stoyanov MIDTERM 2: solutions Score:[ /60] 1. A fair coin is tossed 10 times. Write down the chance of getting exactly 2 heads in the rst 5 tosses, and exactly 1 head in the next 5 tosses. (3 points) Version 2:A fair coin is
School: Berkeley
Review problems for MT 1 S.M. Stoyanov 1. Given below is a distribution table for the 1993 salaries (in thousands of dollars) of the top 60 small companies (according to Forbes magazine). Each interval contains the right endpoint and not the left. You can
School: Berkeley
STATISTICS 21 Fall 2012 S. M. Stoyanov MIDTERM 2 : Solutions Score:[ 1. Use the box 0 0 0 0 0 1 /60] to answer the following questions. Circle the appropriate option, and EXPLAIN your answer. (3 points each) (a) Four draws are made at random with replacem
School: Berkeley
Statistics 21 Fall 2013 Shobhana M. Stoyanov Midterm 1 : Solutions (Both versions) Score:[ Page Score = /60] /15 1. You can nd a list of the CEOs with the highest compensations on the internet at various sites. Interestingly, the list seems to be site-dep
School: Berkeley
Review problems for MT 1 (with solutions) S.M. Stoyanov 1. Given below is a distribution table for the 1993 salaries (in thousands of dollars) of the top 60 small companies (according to Forbes magazine). Each interval contains the right endpoint and not
School: Berkeley
School: Berkeley
School: Berkeley
Review problems for MT 1 S.M. Stoyanov 1. Given below is a distribution table for the 1993 salaries (in thousands of dollars) of the top 60 small companies (according to Forbes magazine). Each interval contains the right endpoint and not the left. You can
School: Berkeley
Review problems for MT 1 (with solutions) S.M. Stoyanov 1. Given below is a distribution table for the 1993 salaries (in thousands of dollars) of the top 60 small companies (according to Forbes magazine). Each interval contains the right endpoint and not
School: Berkeley
Introductory Probability and Sta1s1cs for Business Stat 21 Fall 2012 Shobhana M. Stoyanov 9/24/2013 Chapters 13,14,15: Probability Also using notes, and S1ciGui Chapter 13: Chance How would you dene chance?
School: Berkeley
Introductory Probability and Sta1s1cs for Business Stat 21 Fall 2013 Shobhana Stoyanov Lecture 6 9/17/2013 Regression: Chapters 10, 11, 12 Correla1on Cau1ons Correla1on only tells you about a linear
School: Berkeley
Introductory Probability and Sta1s1cs for Business Stat 21 Fall 2012 Shobhana M. Stoyanov 9/24/2012 Chapters 13,14,15: Probability Also using notes, and S1ciGui Chapter 13: Chance How would you dene chance?
School: Berkeley
Introductory Probability and Sta1s1cs for Business Stat 21 Fall 2013 Shobhana Stoyanov Lecture 3 9/05/2013 Chapter 4, 5 9/5/13 Stat 21 Fall2013 1 Percen1les: Example Consider the following ordered list o
School: Berkeley
Introductory Probability and Sta1s1cs for Business Stat 21 Fall 2013 Shobhana Stoyanov Lecture 4 9/10/2013 Chapter 8: Correla1on Correla1on So far: looked at one variable e.g. Height Now: explore rela1onshi
School: Berkeley
Stat 21: Sampling: Chapter 20 Shobhana Stoyanov Dept of Statistics November 6, 2013 Shobhana Stoyanov Stat 21: Sampling: Chapter 20 1 Example Types of sampling: We want to survey a random sample of 300 passengers on a ight from LA: 1 Randomly generate a l
School: Berkeley
Introductory Probability and Sta1s1cs for Business Stat 21 Fall 2013 Shobhana Stoyanov Lecture 1 8/29/2013 Introduc1on, chapters 3, 4 9/2/13 Stat 21 Fall2012 Shobhana Stoyanov 1 Exploratory Data Analysis
School: Berkeley
Introductory Probability and Sta1s1cs for Business Stat 21 Fall 2012 Shobhana M. Stoyanov 11/21/2013 Chapters 21, 23: Accuracy of our es1mates Also known as Condence Intervals Sta1s1cal Inference 0-1 boxes Fi
School: Berkeley
Introductory Probability and Statistics for Business Stat 21 Fall 2013 Shobhana M. Stoyanov 11/05/2013 Chapter 19 : Sampling Gallup: Example Survey Methods Results are based on telephone interviews conducted as part of Gallup Daily tracking Oct. 22-23, 20
School: Berkeley
Stat 21 Instructor : Shobhana M. Stoyanov Fall 2013 Chap 13
School: Berkeley
Introductory Probability and Sta1s1cs for Business Stat 21 Fall 2013 Shobhana Stoyanov Lecture 2 9/03/2013 Chapters 3, 4 9/3/13 Stat 21 Fall2013 1 Recap of last lecture Variables can be classied as cat
School: Berkeley
Stat 21 Fall 2013: Review problems for the nal 1. Given below is a distribution table for the 1993 salaries (in thousands of dollars) of the top 60 small companies (according to Forbes magazine). Each interval contains the right endpoint and not the left.
School: Berkeley
Course: Statistics For Business Majors
Stat 2 Fall 2010: Midterm Review Answers S.M. Stoyanov 1. (a) Experiment (b) Study (c) Experiment (d) Study (e) Study 2. (a) (ii) There is no spread. (b) (iii) If the square root of a non-negative number is 0, the number must be 0. 3. (a) Drawn in class.
School: Berkeley
Grinstead and Snells Introduction to Probability The CHANCE Project1 Version dated 4 July 2006 Copyright (C) 2006 Peter G. Doyle. This work is a version of Grinstead and Snells Introduction to Probability, 2nd edition, published by the American Mathematic
School: Berkeley
Stat 155 Fall 2011: Proof of the Tartan Theorem Michael Lugo September 23, 2011 Ferguson states but does not prove the Tartan Theorem; he leaves the proof as an exercise (Chapter I.5 exercise 7). I didnt assign that exercise but I thought some people migh
School: Berkeley
Stat 155 Fall 2011: Ruler Michael Lugo September 21, 2011 In class we discussed the game of Ruler. This is the coin-turning game in which any number of coins can be turned over, so long as those coins are consecutive. This gives g (n) = mexcfw_0, g (n 1),
School: Berkeley
Stat 155 Fall 2011: Kayles Michael Lugo September 14, 2011 In class we discussed the game of Kayles and I gave a sketch of a proof that its SpragueGrundy function is eventually periodic. I gave a sketch of the proof and some people were interested in the
School: Berkeley
Some Chip Transfer Games Thomas S. Ferguson University of California, Los Angeles Abstract: Proposed and investigated are four impartial combinatorial games: Empty & Transfer, Empty-All-But-One, Empty & Redistribute, and Entropy Reduction. These games inv
School: Berkeley
Course: Introduction To Probability And Statistics
OVERVIEW OF PROBABILITY, WITH PRACTICE PROBLEMS Ive xed the solution to problem 2c and 3b. I added a question 3c, since my old solution to 3b was actually answering this. The probability of an event A is dened as outcomes corresponding to A P (A) = all po
School: Berkeley
Course: Introduction To Probability And Statistics
MIDTERM REVIEW 1. I record daily high temperatures in Berkeley for 90 days. The average of the rst 30 days is 70 degrees Fahrenheit with an SD of 8 degrees. In the next 60 days, the average is 60 degrees with an SD of 6 degrees. (a) What is the average te
School: Berkeley
Course: Introduction To Probability And Statistics
STAT 131A MIDTERM REVIEW 2. In a study of blood pressure and number of children, it turns out that there is a strong positive correlation between blood pressure and how many children they have. True or False: a. People with high blood pressure tend to hav
School: Berkeley
Psych 133 Allison Harvey Section Friday 1 2 pm Hyunjoong Joo 23208055 Reaction Paper of Sleep and youth suicidal behavior: a neglected eld Sleep undergoes continuous changes during puberty and additionally, suicide risks begin to escalate during this peri
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
v ~ ~- Jk_ Yu~ ~-+- l J& c+-e ~ & ~-~-~ sh(/cfw_1 ~ ~/s /U~ (l[J_;_I_o_ _ ;/lk _ ~1J~- I/J10d? /178 /() if_ ( ;1 _ :-.mJe_- _ )_fL~ft-r-~fce ~-('~ q~- - - - 01~ jv;/ how O!c-1-utA (c-r~Aud . -+-gj_ 1/t_Q - - - - tJ t1rlf;7; -Jt&z ;v; -~- - - - - - - - -
School: Berkeley
Course: Game Theory
Game Theory, Alive Anna R. Karlin and Yuval Peres Draft January 20, 2013 Please send comments and corrections to karlin@cs.washington.edu and peres@microsoft.com i We are grateful to Alan Hammond, Yun Long, Gbor Pete, and Peter a Ralph for scribing early
School: Berkeley
School: Berkeley
AverageSoFar 58.33 58.00 57.67 57.33 57.33 57.33 57.00 56.83 56.67 56.67 56.50 56.33 56.33 56.33 56.17 56.00 56.00 55.67 55.67 55.50 55.33 55.33 55.33 55.33 55.17 55.00 54.83 54.67 54.50 54.33 54.33 54.00 54.00 53.83 53.83 53.67 53.67 53.50 53.33 53.33 53
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 24: 2 Testing Tessa L. Childers-Day UC Berkeley 5 August 2014 Recap Test for Distribution Test for Independence Recap: Hypothesis Testing Steps in Hypothesis Testing: 1 State the hypotheses Null: The di
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 23: Two Sample Testing Tessa L. Childers-Day UC Berkeley 4 August 2014 Recap Surveys Experiments Recap: Hypothesis Testing Steps in Hypothesis Testing: 1 State the hypotheses Null: The dierence between
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 25: Pitfalls and Limits In Testing Tessa L. Childers-Day UC Berkeley 6 August 2014 Recap Interpreting Signicance Data Snooping Role of Model Questions Matter Recap: Hypothesis Testing Steps in Hypothesi
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 22: Hypothesis Testing Tessa L. Childers-Day UC Berkeley 31 July 2014 Recap Examples Recap: Hypothesis Testing Steps in Hypothesis Testing: 1 State the hypotheses Null: The dierence between the sample a
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 21: Intro to Hypothesis Testing Tessa L. Childers-Day UC Berkeley 30 July 2014 Recap Natural Questions Hypothesis Testing Example Recap: From Samples to Boxes Spent the past 3 days reasoning from a samp
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 20: Condence Intervals for Averages Tessa L. Childers-Day UC Berkeley 29 July 2014 Recap Known Box Unknown Box SE Summary Recap: 0-1 Box Yesterday we saw a 0-1 box: Composition unknown Took SRS from box
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 19: Condence Intervals for Percentages Tessa L. Childers-Day UC Berkeley 28 July 2014 Recap Unknown Box Condence Intervals Examples By the end of this lecture. You will be able to: Estimate a 0-1 box mo
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 18: Simple Random Sampling Tessa L. Childers-Day UC Berkeley 24 July 2014 Recap Simple Random Samples EV and SE Examples By the end of this lecture. You will be able to: Draw box models for real-world s
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 17: Using the Normal Curve with Box Models Tessa L. Childers-Day UC Berkeley 23 July 2014 Todays Goals Probability Histograms Probability Histogram Normal Curve Central Limit Theorem By the end of this
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 16: More Box Models Tessa L. Childers-Day UC Berkeley 22 July 2014 Todays Goals EV and SE Normal Curve Classifying and Counting By the end of this lecture. You will be able to: Determine what we expect
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 13: Binomial Formula Tessa L. Childers-Day UC Berkeley 14 July 2014 Todays Goals Recap Counting Calculating Probabilities Examples By the end of this lecture. You will be able to: Calculate the ways an
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 15: Law of Averages Tessa L. Childers-Day UC Berkeley 21 July 2014 Todays Goals Recap Law of Averages Box Models By the end of this lecture. You will be able to: Relate the law of averages to the deniti
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 14: Exam 1 Review Tessa L. Childers-Day UC Berkeley 15 July 2014 Exam 1 Guidelines Material Covered Q&A Details Wednesday, 16 July 2014 In lecture, this room Lasts 80 minutes (9:10am to 10:30am) Worth 3
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 12: More Probability Tessa L. Childers-Day UC Berkeley 10 July 2014 Todays Goals Recap More Rules and Techniques Examples By the end of this lecture. You will be able to: Use the theory of equally likel
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 10: Errors in Regression Tessa L. Childers-Day UC Berkeley 8 July 2014 Todays Goals Why error? Estimation/Interpretation Residuals Strip Methods By the end of this lecture. You will be able to: Decide i
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 6: Normal Curve/Approximation Tessa L. Childers-Day UC Berkeley 1 July 2014 Todays Goals Normal Curve Approx. Normal Data Finding Areas Finding Percentiles By the end of this lecture. You will be able t
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 8: Bivariate Data and Correlation Tessa L. Childers-Day UC Berkeley 3 July 2014 Todays Goals Summary Statistics Association Correlation Properties By the end of this lecture. You will be able to: Constr
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 9: Regression Methods Tessa L. Childers-Day UC Berkeley 7 July 2014 Todays Goals The Intuition The Mechanics Some Caveats Simplication By the end of this lecture. You will be able to: Decide if regressi
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 11: Introduction to Probability Tessa L. Childers-Day UC Berkeley 9 July 2014 Todays Goals What is probability? Box Models Probability Rules By the end of this lecture. You will be able to: Decide which
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 7: Measurement Error Tessa L. Childers-Day UC Berkeley 2 July 2014 Todays Goals Repeated Measurements Outliers Errors By the end of this lecture. You will be able to: Explain why we measure repeatedly C
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 5: Summary Statistics Tessa L. Childers-Day UC Berkeley 30 June 2014 Todays Goals Shape Location Spread By the end of this lecture. You will be able to: Describe a data set by its: Shape Location Spread
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 3: Types of Data and Displays Tessa L. Childers-Day UC Berkeley 25 June 2014 Todays Goals Kinds of Data Displaying Qualitative Data By the end of this lecture. You will be able to: Dene data types Class
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 1: Experimental and Observational Studies Tessa L. Childers-Day UC Berkeley 23 June 2014 Todays Goals Course Introduction Experiments and Observations By the end of this lecture. You will know who I am
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 4: Data Displays (cont.) Tessa L. Childers-Day UC Berkeley 26 June 2014 Todays Goals Recap Displaying Quantitative Data By the end of this lecture. You will be able to: Comprehend displays of quantitati
School: Berkeley
Stat 20: Intro to Probability and Statistics Lecture 2: Surveys and Sampling Tessa L. Childers-Day UC Berkeley 24 June 2014 Todays Goals Survey Basics and Language Types of Surveys Examples By the end of this lecture. You will be able to: Recognize the si
School: Berkeley
Describing*distribu.ons*with*numbers* Describing*distribu.ons*with* numbers* Stat*20,*Fa*12* Noureddine*El*Karoui* A*measure*of*center:*the*mean* *Mean*is*average*value*of*date.*Other*measures* of*center*are*possible* Deni.on:* The*mean*of*n*observa.ons*x
School: Berkeley
Bayes rule: updating probabilities as new information is acquired. Abstract set-up: Partition (B1 , B2 , . . .) of alternate possibilities. Know prior probabilities P (Bi ). Then observe some event A happens (the new information) for which we know P (A|Bi
School: Berkeley
Events A and B are independent if: knowing whether A occured does not change the probability of B . Mathematically, can say in two equivalent ways: P ( B | A) P (A and B ) = P (B A) = P (B ) = P ( B ) P ( A) . Important to distinguish independence from mu
School: Berkeley
Lecture 2 Very simple problems can be done in the bare hands: way write down all possible outcomes P (A) = probability event A happens = sum of the probabilities of the outcomes that make A happen. For more complicated problems we need to use rules of pro
School: Berkeley
Google Aldous STAT 134 to nd course web page. [show page] Style of course Blackboard and chalk (except rst 5 lectures). We study the basic mathematics of probability . . . . . . but its not just algebra/calculus; you need to constantly think what the math
School: Berkeley
Course: Probability
Bayes rule: updating probabilities as new information is acquired. (silly) Example There are 2 coins: one is fair: P (Heads) = 1/2 one is biased: P (Heads) = 9/10 Pick one coin at random. Toss 3 times. Suppose we get 3 Heads. What then is the chance that
School: Berkeley
Course: Probability
Balls in boxes; visual model covers many different stories. N boxes and k balls. Put each ball independently into a random box. Well study the event Ak : rst k balls all in dierent boxes. 1 P (A2) = NN 2 P (A3|A2) = NN 3 P (A4|A3) = NN . P (Ak |Ak1) = N (
School: Berkeley
Course: Probability
Example Know a family has 2 children, and know at least one child is a girl. What is the chance the other child is a girl? Cant answer; it depends on how we got this information. (1) Computer list story; chance = 2/3 (2) Park story; chance = 1/2 1 The Mon
School: Berkeley
Course: Probability
PROPORTIONS Set S = cfw_students in this room. Typical subsets A = cfw_men; B = cfw_Stat majors; C = cfw_CS majors. For any subset A write P R(A) = #A/#S. Numerical values of P R(A), P R(B), P R(C) . . . are empirical facts. But logic/arithmetic tells us
School: Berkeley
Course: Probability
Google Aldous STAT 134 to nd course web page. [show page] Style of course Blackboard and chalk (except rst 5 lectures). We study the basic mathematics of probability . . . . . . but its not just algebra/calculus; you need to constantly think what the math
School: Berkeley
Course: Probability
Complex Coupling ! singlet! doublet! triplet! ?! quartet! Successive Application of the N + 1 Rule! HB HA HB Cl Cl Cl TMS 6ppm 5ppm 4ppm 3ppm 1ppm 2ppm 0 ppm Two different hydrogen atoms coupling to a third hydrogen atom! HA What if:! JAB = 3 Hz! JAC = 8
School: Berkeley
Course: Probability
Spin-Spin Splitting ! (J Coupling)! Coupling of spins provides connectivity information ! about neighboring nuclei! 1H NMR Spectrum of 1,1,2-trichloroethane! HB Predicted ! HA H B! Cl HB Cl Cl HA! TMS 6ppm 5ppm 4ppm 3ppm 2ppm 1ppm 0 ppm Observed! ! TMS 6p
School: Berkeley
Course: Probability
Structure Determination! v NMR Spectroscopy! v Mass Spectrometry! v X-Ray Crystallography! Spectroscopy! Absorption of Electromagnetic Radiation:! Something Changes from a Lower Energy ! State to a Higher Energy State! E = h ! E: change in energy h : Plan
School: Berkeley
Course: Probability
Retention Factor (Rf)! Not a Physical Constant! Rf = ! distance to ! midpoint! of spot! distance to ! solvent front! Rf depends on:! u The stationary phase ! u The mobile phase ! u The amount of compound! spotted! u The temperature! TLC: Conclusions! Give
School: Berkeley
Course: Probability
Chromatography! Separation of Different Compounds! ! ! ! Partition! Adsorption! Adsorption Chromatography! Compounds that have Different Interactions with the Mobile Phase ! Versus the Stationary Phase can be Separated ! ABC ABA C C CB BA add solvent st
School: Berkeley
Course: Probability
Purifying Solids! ! ! ! Sublimation/Deposition! Chromatography! Recrystallization! Recrystallization! Step 1: Choosing the right equipment! The Glassware! Erlenmeyer ask! Richard Erlenmeyer! Test tube! Constricted opening! Large surface area! Step 1:
School: Berkeley
Course: Probability
Boiling Points Impurities and Boiling Points Soluble, Non-Volatile Impurity PA = vapor pressure of compound A in a solution of A and a soluble impurity Pressure Raoults Law: PA = XAPA E Liquid Solid Patm D T C Gas Reduced vapor pressure curve due to the
School: Berkeley
Course: Probability
Melting Points Typical Phase Changes as a Function of Temperature at a Constant Pressure Temperature D bp, cp B mp, fp E L C G Gas (G) Liquid Solid A S L (L) (S) Heat Added BC = melting point(mp)/freezing point(fp): [Psolid = Pliquid] DE = boiling point(b
School: Berkeley
Course: Probability
Terminology of Mixing Solution: A homogenous mixture of two or more compounds. Solute: The compound in a solution present in lesser amount. Solvent: The major component of a solution. Miscibility: Two components of a solution are innitely soluble in each
School: Berkeley
Course: Probability
Intermolecular Forces! Intermolecular forces take place between molecules.! ! ! ! ! An understanding of intermolecular forces is crucial ! to a chemists ability to successfully carry out reactions ! in the organic chemistry laboratory.! ! The Forces Betwe
School: Berkeley
Announcements: Regina Wu, Hana Ueda, and John Jimenez will be helping to answer your questions on bSpace and in lab. Homework 1 is due next Wednesday night. There have been some problems on bSpace. Please make sure you get a verication email when you uplo
School: Berkeley
Announcement: There will be another Short Assignment posted later today and due Monday night. Todays topics Data structures galore: matrices, arrays, data frames, and lists More ways to operate efciently on entire data structures and avoid looping Thurs
School: Berkeley
A few announcements: If you havent gotten your computer account, be sure to email Daisy (yanhuang@stat.berkeley.edu) ASAP. If you are just joining the course this week, please see me after class, in ofce hours, or send me an email if you have not done so
School: Berkeley
Course: Stochastic Processes
Lecture 6 : Markov Chains STAT 150 Spring 2006 Lecturer: Jim Pitman Scribe: Alex Michalka <> Markov Chains Discrete time Discrete (finite or countable) state space S Process cfw_Xn Homogenous transition probabilities matrix P = cfw_P (i, j); i, j S P (i,
School: Berkeley
Course: Stochastic Processes
Lecture 21 : Continuous Time Markov Chains STAT 150 Spring 2006 Lecturer: Jim Pitman Scribe: Stephen Bianchi <> (These notes also include material from the subsequent guest lecture given by Ani Adhikari.) Consider a continuous time stochastic process (Xt
School: Berkeley
Course: Stochastic Processes
Lecture 17 : Long run behaviour of Markov chains STAT 150 Spring 2006 Lecturer: Jim Pitman Scribe: Vincent Gee <> Basic Case: S is finite Markov matrix is P Assume that for some power of P has all entries > 0: k such that P k (i, j) > 0i, j S Such P is c
School: Berkeley
Course: Stochastic Processes
Lecture 17 : Long run behaviour of Markov chains STAT 150 Spring 2006 Lecturer: Jim Pitman Scribe: Vincent Gee <> Basic Case: S is finite Markov matrix is P Assume that for some power of P has all entries > 0: k such that P k (i, j) > 0i, j S Such P is c
School: Berkeley
Course: Stochastic Processes
STAT 150 CLASS NOTES Onur Kaya 16292609 May 18, 2006 Martingales: A sequence of random variables (Mn ) is a martingale relative to the sequence (Xn ) if: 1. Mn is some measurable function of X1 , X2 ,., Xn 2. E[Mn+1 |X1 , X2 , ., Xn ] = Mn Notice that (1)
School: Berkeley
Course: Stochastic Processes
Stat 150 Stochastic Processes Spring 2009 Lecture 4: Conditional Independence and Markov Chain Lecturer: Jim Pitman 1 Conditional Independence Q: If X and Y were conditionally independent given , are X and Y independent? (Typically no.) Y Write X Z to in
School: Berkeley
Course: STAT 21
Quiz 1 Statistics 21 Spring 2010 Ibser 1. A large class takes a test, and the table shows their scores. For all parts of this problem, assume that the scores are continuous and that they are evenly distributed within each separate class interval. The maxi
School: Berkeley
Course: Intro To Probability And Statistics
Statistics 20: Summer Session 2007 Quiz n. 1 Friday July 6, 2007 Full Name (Please print): ID: Lab: YOU MUST SHOW WORK TO RECEIVE ANY CREDIT 1. The British government conducts regular surveys of household spending. The average weekly household spending on
School: Berkeley
UGBA 103, Midterm Exam: March 05, 2012 Name: ID: Section: The answers on this midterm are entirely my own work. I neither gave nor received any aid while taking this midterm. _ Signature Please remember to write your name legibly on every page. The maximu
School: Berkeley
Course: Probability
Statistics 2 Problems from past nal exams 1. (5 points) The paragraph below is taken from an article in the San Francisco Chronicle of Tuesday, March 21, 1995. The person quoted in the article is Patrick Portway, executive director of the United States Di
School: Berkeley
STAT 20 - Fall 2011 - Practice Midterm 1 Most explanations require just a sentence or two. On calculations, show your work and work through to a numerical answers, upto at least 2 decimal places. 1. Below are the statistics of 3 lists of numbers. The aver
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Practice Midterm 2 1. We surveyed 100 women about their weights and heights, and got the following results; average height = 64 inches, average weight = 140 pounds, SD = 4 inches SD = 15 pounds The correlation coecient r between the heights and weights wa
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
MIDTERM 2 04/16/2014 Olena Blumberg Name: GSI and Section #: Show your work for all the problems. Good luck! 1. We surveyed 100 men about their weights and heights, and got the following results: average height = 69 inches, average weight = 170 pounds, SD
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
FINAL EXAM 05/14/2014 Olena Blumberg Name: GSI and Section #: Show your work for all the problems. Good luck! 1. In a certain school district, about 7% of the students are homeschooled, and the remaining 93% go to conventional schools. The average SAT sco
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
FINAL EXAM 05/14/2014 Olena Blumberg Name: GSI and Section #: Show your work for all the problems. Good luck! 1. [5 pts] A researcher is interested in whether more sleep boosts the immune system. So she calls a random sample of 400 people and asks them ho
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
FINAL EXAM 05/14/2014 Olena Blumberg Name: GSI and Section #: Show your work for all the problems. Good luck! 1. In a certain school district, about 7% of the students are homeschooled, and the remaining 93% go to conventional schools. The average SAT sco
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Practice Midterm 1 1. According to an observational study done at Kaiser Permanente in Walnut Creek, California, users of oral contraceptives have a higher rate of cervical cancer than non-suers, even after adjusting for age, educations, marital status, r
School: Berkeley
STATISTICS 21 Fall 2012 S. M. Stoyanov MIDTERM 1 Score:[ /60] Please show ALL WORK AND REASONING for ALL the problems.You may NOT use a programmable calculator for this quiz. Do NOT ROUND the numbers in the middle of a problem. In general, unless asked to
School: Berkeley
STATISTICS 21 Fall 2012 S. M. Stoyanov MIDTERM 2 Score:[ Name: /60] SID: Section: Please circle your sections GSI: Tina Ansari Nathan Cheung Andrew Kwong Nazret Weldeghiorgis Susannah Lee Arie Wong Please show ALL WORK AND REASONING for ALL the problems.Y
School: Berkeley
Statistics 21 Fall 2012 Shobhana M. Stoyanov Midterm 2 Score:[ Name: /60] SID: Section: Please circle your sections GSI: Tina Ansari Nathan Cheung Andrew Kwong Nazret Weldeghiorgis Susannah Lee Arie Wong Please show ALL WORK AND REASONING for ALL the prob
School: Berkeley
Statistics 21 Fall 2012 Shobhana M. Stoyanov Midterm 1: Answers Score:[ /60] Please show ALL WORK AND REASONING for ALL the problems.You may NOT use a programmable calculator for this quiz. Do NOT ROUND the numbers in the middle of a problem. In general,
School: Berkeley
STATISTICS 21 FALL 2013 S. M. Stoyanov MIDTERM 2: solutions Score:[ /60] 1. A fair coin is tossed 10 times. Write down the chance of getting exactly 2 heads in the rst 5 tosses, and exactly 1 head in the next 5 tosses. (3 points) Version 2:A fair coin is
School: Berkeley
STATISTICS 21 Fall 2012 S. M. Stoyanov MIDTERM 2 : Solutions Score:[ 1. Use the box 0 0 0 0 0 1 /60] to answer the following questions. Circle the appropriate option, and EXPLAIN your answer. (3 points each) (a) Four draws are made at random with replacem
School: Berkeley
Statistics 21 Fall 2013 Shobhana M. Stoyanov Midterm 1 : Solutions (Both versions) Score:[ Page Score = /60] /15 1. You can nd a list of the CEOs with the highest compensations on the internet at various sites. Interestingly, the list seems to be site-dep
School: Berkeley
School: Berkeley
Stat 20 Fall 06 A. Adhikari ANSWERS TO PRACTICE QUESTIONS FOR THE FINAL 1. The box has 155 tickets. Each ticket has two parts: the left side shows the 1/0 that will be the result if the patient gets assigned to the treatment group, and the right side show
School: Berkeley
Stat 20 Fall 06 A. Adhikari PRACTICE QUESTIONS FOR THE FINAL Important: Some of the problems below are standard applications of the techniques of the class, and others require a little more thought to decide which technique, if any, to use. The focus in t
School: Berkeley
Course: Probability
UNIVERSITY OF CALIFORNIA, BERKELEY DEPARTMENT OF STATISTICS STAT 134: Concepts of Probability Spring 2014 Instructor: Antar Bandyopadhyay Solution to the Final Examination 1. State whether the following statements are true or false. Write brief reasons su
School: Berkeley
Course: Probability
UNIVERSITY OF CALIFORNIA, BERKELEY DEPARTMENT OF STATISTICS STAT 134: Concepts of Probability Spring 2014 Instructor: Antar Bandyopadhyay Solution to the Midterm Examination 1. A point (X, Y ) is randomly selected from the following nite set of points on
School: Berkeley
Course: Probability
UNIVERSITY OF CALIFORNIA, BERKELEY DEPARTMENT OF STATISTICS STAT 134: Concepts of Probability Spring 2014 Instructor: Antar Bandyopadhyay Practice Final Examination (I) Date Given: April 25, 2014 Duration: 180 minutes Total Points: 100 Note: There are ten
School: Berkeley
Course: Probability
UNIVERSITY OF CALIFORNIA, BERKELEY DEPARTMENT OF STATISTICS STAT 134: Concepts of Probability Spring 2014 Instructor: Antar Bandyopadhyay Practice Final Examination (II) Date Given: April 25, 2014 Duration: 180 minutes Total Points: 100 Note: There are te
School: Berkeley
Course: Probability
UNIVERSITY OF CALIFORNIA, BERKELEY DEPARTMENT OF STATISTICS STAT 134: Concepts of Probability Spring 2014 Instructor: Antar Bandyopadhyay Practice Midterm Examination Date Given: March 10, 2014 Duration: 80 minutes Total Points: 60 Note: There are ve prob
School: Berkeley
Course: Game Theory
Stat 155 Midterm Practice Solutions Problems: Attempt all questions and show your working - solutions without explanation will not receive full credit. One double sided sheets of notes are permitted. Q 1 Find the value and optimal strategy of the followin
School: Berkeley
Course: Game Theory
Stat 155 Midterm Spring 2014 Name: SID: This exam has 5 problems and a total of 75 points. Attempt all questions and show your working - solutions without explanation will not receive full credit. One double sided sheets of notes are permitted. Answer que
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Stat 20 Quiz 5 April 23, 2014 Name: _ Section: 101, 102, 103, 104 105, 106, 107, 108 SOLUTIONS 8 points possible Part 1 Show all work and put a box around your answer. Provide explanations when youre asked. 1. A recent survey estimated the US per capita c
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Stat20 Quiz4 April9,2014 Name:_Section:101, 102,103,104 105,106,107,108 SOLUTIONS10pointspossible Part1Showallworkandputaboxaroundyouranswer.Provideexplanationswhenyoure asked. 1. Aboxcontainsanequalnumberofredmarblesandbluemarbles.500drawsaremade fromthe
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Solutions: PartI a.Nullhypothesis:samplemean(fromuniversity)=meanofstate(populationmean) alternatehypothesis:samplemeanisgreaterthanmeanofstate(populationmean) #samples=46,populationmean=12400,samplemean=13445,sdofsample=1800 SEforavg=1800/sqrt(46)=265.39
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Stat20 Quiz2 February24,2014 Name:_Section:101, 102,103,104 105,106,107,108 SOLUTIONS?pointspossible Part1Forquestions12,showallworkandputaboxaroundyouranswer.Forquestion3,no workisrequired.UsetheprovidedNormalTableonthebackifneeded. 1. ForfreshmenatUCBer
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Stat 20 Quiz 3 March 10, 2014 Name:_Section:101,102,103,104 105,106,107,108 1.Astatisticsclassisunhappywithitsmidtermperformance.Theclassmanagestopersuadetheprofessortogiveallthe studentstheopportunitytotakearetest.Twoscoreswillbepositivelyandlinearlycorr
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Midterm Exam Instructor: Tessa Childers-Day Stat 20 11 March 2014 Please write your name and student ID below, and circle your section. With your signature, you certify that you have not observed poor or dishonest conduct on the part of your classmates. Y
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Midterm Exam Instructor: Tessa Childers-Day Stat 20 1 May 2014 Please write your name and student ID below, and circle your section. With your signature, you certify that you have not observed poor or dishonest conduct on the part of your classmates. You
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Stat 20 Quiz 1 February 10, 2014 Please write your name below and circle your section. Answer the questions in the space provided. There are questions on the back. This quiz covers material from Homeworks 1 a
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Midterm Exam Instructor: Tessa Childers-Day Stat 20 11 March 2014 Please write your name and student ID below, and circle your section. With your signature, you certify that you have not observed poor or dishonest conduct on the part of your classmates. Y
School: Berkeley
Course: INTRODUCTION TO PROBABILITY AND STATISTICS
Midterm Exam Instructor: Tessa Childers-Day Stat 20 1 May 2014 Please write your name and student ID below, and circle your section. With your signature, you certify that you have not observed poor or dishonest conduct on the part of your classmates. You
School: Berkeley
Course: Probability
Stat 134: problems before the nal exam Michael Lugo May 6, 2011 Some problems recommended to do before the nal exam: 6.4.6, 6.4.9, 6.4.12, 6.4.21, 6.5.2, 6.5.4, 6.5.6, 6.5.8, 6.R.8(c), 6.R.13(b), 6.R.14, 6.R.18, 6.R.25 6.4.6 Let X1 and X2 be the numbers o
School: Berkeley
Course: Probability
Stat 134: problems before the second exam Michael Lugo March 27, 2011 4.4.4 You can use the formula of example 5 here: fY (y ) = (fX ( y ) + fX ( y )/(2 y ). Here fX (x) = 1/2 if 1 x 1, and 0 otherwise. So fY (y ) = (1/2 + 1/2)/(2 y ) = 1/(2 y ) if 0 y 1,
School: Berkeley
Course: Statistics For Business Majors
Stat 21 Quiz #3 October 12, 2011 Name_ Section#_ VERSION A 1.Xisarandomvariabledefinedas: x 1 0 1 P(x) .35 .5 .15 A)Drawthecumulativedistributionfunction(cdf)forX. B)Evaluate: i)P(X1.8)=0 ii)P(X2.3)=0 iii)P(X0.5)=0.15 D)Calculate: i)E(X)=-0.2 X 1 0 1 E
School: Berkeley
Course: Statistics For Business Majors
Stat 21, Fall 2011, Murali-Stoyanov Quiz 2 (v1) Answer Key 1a) (70-79)/8.5 = -1.06 ~ -1.05. Area = 70.63% (85-79)/8.5 = 0.71 ~ 0.70. Area = 51.61% (70.63%/2) + (51.61%/2) = 61.12% 1b) 35th Percentile -> Area = 30% (82-79)/8.5 = 0.35. Area = 27.37% (30%/2)
School: Berkeley
Course: Concepts Of Probability
Stat 134 Midterm Spring 2013 Instructor: Allan Sly Name: SID: There are 4 questions worth a total of 30 points. Attempt all questions and show your working (except in Question 1). Answer the questions in the space provided. Additional space is available a
School: Berkeley
Course: Intro To Probability And Statistics
Statistics 20: Midterm Solutions Summer Session 2007 1. [20 points] Pressure and Boiling Points. (a) [5 points] What is the equation of the regression line for predicting P RES from T EMP ? Solution: Here the x variable is TEMP in Fahrenheit and the y var
School: Berkeley
Chapter4 4.1 a)Definitions b)Procedureandsteptostepsolvingproblems 4.2 a)Errortype1anderrortype2 4.3 a) LargesampletestofHypothesisaboutP 4.4 a)Twopopulationsmeanflowchart b)Formulaandstepbystepsolvingproblems c)IndependentandDependent d)Determinationofsa
School: Berkeley
Course: Stochastic Processes
STAT 150 SPRING 2010: MIDTERM EXAM Problems by Jim Pitman. Solutions by George Chen 1. Let X0 , Y1 , Y2 , . . . be independent random variables, X0 with values in cfw_0, 1, 2, . . . and each Yi an indicator random variable with P (Yi = 1) = 1 and P (Yi =
School: Berkeley
STAT 20, Fall 2012 Instructor: Noureddine El Karoui Practice Quiz 1 Partial credit will be given. Short answers are ok; they just need to be to the point. Show your work and justify your answers. Good luck! Name: Student ID: Score: Do not reproduce or put
School: Berkeley
STAT 20, Fall 2010 Midterm Partial credit will be given. Short answers are ok; they just need to be to the point. Show your work and justify your answers. Good luck! Name: Student ID: Score: Problem 1 Discuss briey the correlation coecient. Give its deni
School: Berkeley
STAT 20, Fall 2010 Final Partial credit will be given. Short answers are ok; they just need to be to the point. The problems are not ordered by diculty. You might want to start by the ones you feel you know most about. Most questions are independent of pr
School: Berkeley
STATISTICS 134 Practice Final There are 9 questions, worth a total of 49 points. Calculations should be worked through to an explicit numerical answer. Show your work! 1. [5 points] Let U be a continuous r.v. with uniform distribution on (0, 1). U Let X =
School: Berkeley
Statistics 134 Fall 2005 Final Exam Professor James Pitman 1. A random variable X with values between -1 and 1 has probability density function f (x) = cx2 for x in that range, for some constant c. (a) Find c as a decimal. (b) Give a formula for the cumul
School: Berkeley
Course: STATISTICS 2
(i) less than 2.9 inches (ii) equal to 2.9 inches (iii) more than 2.9 inches
School: Berkeley
Course: Introduction To Probability And Statistics
STAT 20 - QUIZ 2 SOLUTIONS Ive provided two normal tables in the back. The rst is a CDF table, so it gives areas to the left of z. The second one is the table from the back of the book (the one we have been using). 1. The midterm and nal scores of a large
School: Berkeley
Course: Introduction To Probability And Statistics
STAT 20 - QUIZ 2 Ive provided two normal tables in the back. The rst is a CDF table, so it gives areas to the left of z. The second one is the table from the back of the book (the one we have been using). 1. The midterm and nal scores of a large class hav
School: Berkeley
Course: Introduction To Probability And Statistics
STAT 20 - QUIZ 1 10 0 5 Percent 15 20 1. The gure below shows the distribution of test scores for an introductory statistics class. The bins include the right endpoint, but not the left (right endpoint convention). 3060 6075 7585 8590 9095 95100 Test scor
School: Berkeley
Course: Introduction To Probability And Statistics
STAT 20 QUIZ 1 - STUDENT SOLUTIONS 10 0 5 Percent 15 20 1. The gure below shows the distribution of test scores for an introductory statistics class. The bins include the right endpoint, but not the left (right endpoint convention). 3060 6075 7585 8590 90
School: Berkeley
Economics 250 Introduction to Finance Midterm (January 30, 2007) Name:_ Student ID:_ Section:_ Question Weight 1 2 3 4 5 6 7 10 10 15 15 15 15 20 Total 100 Score 1. Short Questions. [10 pts] (a) Consider two bonds that are equivalent in maturity and face
School: Berkeley
STAT516 Solution to Homework 2 1.4.5: a) Let U1=(urn 1 chosen), U2=(urn 2 chosen), B=(black ball chosen), W=(White ball chosen). 2/5 B 1/2 U1 3/5 4/7 W B 1/2 U2 3/7 W b) P(U1)=1/2=P(U2); P(W|U1)=3/5; P(B|U1)=2/5; P(W|U2)=3/7; P(B|U2)=4/7 c) P(B)=P(B|U1)P(
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Problem Set 5 Fall 2011 Issued: Thursday, November 10, 2011 Due: Wednesday, November 30, 2011 Problem 5.1 Conv
School: Berkeley
Course: 135
Stat 135, Fall 2011 A. Adhikari HOMEWORK 5 (due Friday 10/7) 1. 9.11. Use R to do the plots accurately. In each case, say what the limiting power is as approaches 0. 2. 9.12. 3. 9.13. In c, use R to nd the critical values x0 and x1 . Turn the page for d.
School: Berkeley
Course: 135
Stat 135, Fall 2011 A. Adhikari HOMEWORK 4 (due Friday 9/30) 1. 8.20. Use R to do this one accurately. Be careful about constants when youre working out the distribution of 2 . 2. 8.32. You dont have to do all six intervals in parts (b) and (c); just do t
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Problem Set 1 Fall 2011 Issued: Thurs, September 8, 2011 Due: Monday, September 19, 2011 Reading: For this pro
School: Berkeley
Statistics 20: Quiz 4 Solutions 1. A team of doctors want to estimate the life expectancy of students afflicted with the rare genetic disease statinotisticitis; however, only 15 known cases have ever been diagnosed. The sample reported a mean lifespa
School: Berkeley
Math 361/Stat 351 X1 Homework 10 Solutions Spring 2003 Graded problems: 1(d), 3(c), 4(b), 7 Problem 1. [4.2.4] Suppose component lifetimes are exponentially distributed with mean 10 hours. Find (a) the probability that a component survives 20 hou
School: Berkeley
Statistics 20: Quiz 1 Solutions Speed (mph) 0-10 10-20 20-40 40-80 80-95 Percentage of Total Cars 20 10 40 20 10 The above table depicts data collected in a (hypothetical) survey studying the distribution of traffic speed on the Bay Bridge. Each gro
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Problem Set 3 Fall 2011 Issued: Monday, October 10, 2011 Due: Monday, October 24, 2011 Reading: For this probl
School: Berkeley
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Solutions to Problem Set 3 Fall 2011 Issued: Monday, October 10, 2011 Due: Monday, October 24, 2011 Reading: F
School: Berkeley
Course: 135
Stat 135, Fall 2011 HOMEWORK 8 due WEDNESDAY 11/9 at the beginning of lecture Friday 11/11 is a holiday, so this is a very short homework due two days earlier at the start of lecture. Grading: A (4 points) for all three problems done well, B (2 points) fo
School: Berkeley
Course: Probability
Homework # 2 Statistics 134, Pitman , Spring 2009 2.1.2 P (2 boys and 2 girls) = 4 (1/2)4 = 6/24 = 0.375 < 0.5. So families with dierent 2 numbers of boys and girls are more likely than those having an equal number of boys and girls, and the relative freq
School: Berkeley
UC Berkeley Department of Electrical Engineering and Computer Science Department of Statistics EECS 281A / STAT 241A Statistical Learning Theory Solutions to Problem Set 1 Fall 2011 Issued: Thurs, September 8, 2011 Due: Monday, September 19, 2011 Reading:
School: Berkeley
Course: 135
Stat 135, Fall 2011 HOMEWORK 1 (due Friday 9/9) 1a) Let x1 , x2 , . . . , xn be a list of numbers with mean and SD . Show that 2 = 1 n n x2 2 i i=1 b) A class has two sections. Students in Section 1 have an average score of 75 with an SD of 8. Students in
School: Berkeley
Course: Introductory Probability And Statistics For Busines
- Home | Text Table of Contents | Assignments | Calculator | Tools | Review | Glossary | Bibliography | System Requirements | Author's Homepage Chapter 21 Testing Equality of Two Percentages Chapter 19, "Hypothesis Testing: Does Chance Explain the Results
School: Berkeley
Math 361 X1 Homework 4 Solutions Spring 2003 Graded problems: 1(b)(d); 3; 5; 6(a); As usual, you have to solve the problems rigorously, using the methods introduced in class. An answer alone does not count. The problems in this assignment are inte
School: Berkeley
Math 361 X1 Homework 6 Solutions Spring 2003 Graded problems: 2(a);4(a)(b);5(b);6(iii); each worth 3 pts., maximal score is 12 pts. Problem 1. [3.1:4] Let X1 and X2 be the numbers obtained on two rolls of a fair die. Let Y1 = max(X1 , X2 ) and Y2
School: Berkeley
Math 361 X1 Homework 9 Solutions Spring 2003 Graded problems: 1(a), 2, 4(b), 5(b) (3 points each - 12 points maximal); 7 (Bonus problem): up to 2 additional points Problem 1. [4.R:25, variant] Suppose U is distributed uniformly on the interval (0
School: Berkeley
Math 361 X1 Homework 8 Solutions Spring 2003 Graded problems: 1, 4(b), 5, 6; 3 points each, 12 points total Problem 1. In a certain math class each homework problem is scored on a 0 3 point scale. A lazy grader decides to grade these problems by
School: Berkeley
Math 361 X1 Homework 1 Solutions Spring 2003 Graded problems: 1; 2(b);3;5; each worth 3 pts., maximal score is 12 pts. Problem 1. A coin is tossed repeatedly. What is the probability that the second head appears at the 5th toss? (Hint: Since only
School: Berkeley
Stat 20 Fall 2006 A. Adhikari Exercises in Probability 1. A die is rolled. Find the chance that a) a six appears for the rst time on the 10th roll. b) it takes more than 10 rolls to get a six. 2. I have two coins. One is fair and the other lands heads wit
School: Berkeley
School: Berkeley
School: Berkeley
Stat 20 Fall 2006 A. Adhikari Answers to Exercises in Probability You must work out the decimal answers. 1a) 0.0323 = (5/6)9 (1/6). b) 0.162 = (5/6)10 . Same as rst 10 rolls do not show any sixes. 2a) The fair coin, because the observation is more likely
School: Berkeley
Course: Probability
Homework # 10 5.1.6 Statistics 134, Bandyopadhyay, Spring 2014 (1/2)132 0.376 152 b) Let F = cfw_rst person arrives before 12:05 and L = cfw_last person arrives after 12:10 Then, a) P (Jack arrives at least two minutes before Jill) = P (F L) = 1 P (F L)c
School: Berkeley
Course: Probability
Homework # 11 4.6.3 Statistics 134, Bandyopadhyay, Spring 2014 a) (y x)n b) (1 x)n (y x)n c) y n (y x)n d) 1 (1 x)n y n + (y x)n e) n k f) n k+1 xk (1 y)nk xk+1 (1 y)nk1 + n k n! xk (1 y)nk + (k)!1!(nk)! xk (y x)(1 y)nk1 4.6.4 a) P (Z = 1) = P (Z = 0) = 1
School: Berkeley
Course: Game Theory
Stat 155 Homework # 10 Due April 29 (Tuesday) Problems: Q 1 Karlin-Peres Chapter 7 Q 7.1 Q 2 For each of the following voting systems on n > 1 voters and q > 2 alternatives, nd rankings such that at least one voter will want to manipulate Almost dictator
School: Berkeley
Course: Game Theory
Stat 155 Homework # 10 Due April 29 (Tuesday) Problems: Q 1 Karlin-Peres Chapter 7 Q 7.1 If the voting in an election with 3 candidates was 35% : A > B > C 35% : B > C > A 30% : C > A > B (1) (2) (3) Then the winning candidate in a runo election is candid
School: Berkeley
Course: Game Theory
Stat 155 Homework # 9 Due April 21 Problems: Q 1 Karlin-Peres Chapter 11 Q 11.1 The men proposing stable matching is A with Y , B with Z and C with X. In the women proposing algorithm is the same. Q 2 Karlin-Peres Chapter 11 Q 11.2 Suppose that man m is m
School: Berkeley
Course: Game Theory
Stat 155 Homework # 8 Due April 14 Problems: Q 1 Karlin-Peres Chapter 3 Q 3.4 Q 2 We introduce a third type to the hawk and dove game called bourgeois which will only ght if it got to the resource rst. If we assume that the bird are equally likely to nd t
School: Berkeley
Course: Game Theory
Stat 155 Homework # 9 Due April 21 Problems: Q 1 Karlin-Peres Chapter 11 Q 11.1 Q 2 Karlin-Peres Chapter 11 Q 11.2 Q 3 Karlin-Peres Chapter 11 Q 11.3 Q 4 There are 4 men, called A, B, C, D and 4 women, called W, X, Y, Z, with the following preference list
School: Berkeley
Course: Game Theory
Stat 155 Homework # 8 Due April 14 Problems: Q 1 Karlin-Peres Chapter 3 Q 3.4 First game (4, 4) (2, 5) (5, 2) (3, 3) Playing strategy B is dominant for both players and so the only Nash equilibrium is x = y = (0, 1). The only pure strategy not equal to x
School: Berkeley
Course: Game Theory
Stat 155 Homework # 7 Due April 7 Problems: Q 1 Karlin-Peres Chapter 3 Q 3.18 Player 1 can travel from A to C via either B or D. Player 2 can travel from B to D via either A or C. The payo matrix of the game is (7, 7) (5, 4) (7, 8) (5, 5) Travelling throu
School: Berkeley
Course: Game Theory
Stat 155 Homework # 7 Due April 7 Problems: Q 1 Karlin-Peres Chapter 3 Q 3.18 Q 2 On a TV show two contestants must choose between 4 with values d1 , d2 , d3 and d4 (you can assume they are all positive). If they choose dierent prizes they both get their
School: Berkeley
Course: Game Theory
Stat 155 Homework # 6 Solutions Problems: Q 1 Ferguson Chapter III Section 2.5 Q 5 By marking the optimal value in each column for player one and the optimal value in each row for player two we can nd the pure strategies. (a) The only pure Nash equilibriu
School: Berkeley
Course: Game Theory
Stat 155 Homework # 5 Due March 3 Problems: Q 1 Ferguson Chapter II Section 2.6 Q 6 (a) Solution 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 The rst and seventh rows are dominated by the second and six
School: Berkeley
Course: Game Theory
Stat 155 Homework # 6 Due March 20 in class (or if you want to do it over spring break on March 31 in section) Problems: Q 1 Ferguson Chapter III Section 2.5 Q 5 Q 2 Karlin-Peres Chapter 3 Q 3.3 Q 3 Karlin-Peres Chapter 3 Q 3.8 Q 4 Karlin-Peres Chapter 3
School: Berkeley
Course: Game Theory
Stat 155 Homework # 5 Due March 3 Problems: Q 1 Ferguson Q 2 Ferguson Q 3 Ferguson Q 4 Ferguson Chapter Chapter Chapter Chapter II II II II Section Section Section Section 2.6 2.6 3.7 3.7 Q Q Q Q 6 (a) 9 2 4 1
School: Berkeley
Course: Game Theory
Stat 155 Homework # 4 Solution Problems: Q 1 Ferguson Chapter II Section 2.6 Q 1 Solution The matrix 1 3 2 2 has no saddle point. Thus applying the formulas for a two by two game, the optimal strategies are 2 (2) (1 (3) 2 1 x=( , )=( , ) (1 (3) + (2 (2) (
School: Berkeley
Course: Game Theory
Stat 155 Homework # 4 Due February 24 Problems: Q 1 Ferguson Chapter II Section 2.6 Q 1 Q 2 Ferguson Chapter II Section 2.6 Q 2 Q 3 Ferguson Chapter II Section 2.6 Q 4 Q 4 Karlin-Peres Chapter 2 Exercise 2.7 1
School: Berkeley
Course: Game Theory
Stat 155 Homework # 2 Due February 10 Problems: Q 1 Consider a 2 person rst price auction with reserve price r (in such an auction the highest bidder pays his bid and wins the item if it is greater than r while if neither bidder bids more than r then no o
School: Berkeley
Course: Game Theory
Stat 155 Homework # 1 Due February 3 Problems: Q 1 Let N be uniform on cfw_1, 2, . . . , 10 and let X be a binomial Bin(N, 1/2). Find the mean and variance of X. Solution Conditional on N = n we have that X is a Bernoulli random variable and so E[X 2 | N
School: Berkeley
Course: Game Theory
Stat 155 Homework # 3 Due February 17 Problems: Q 1 Ferguson Chapter I Section 1.5 Q 4 Q 2 Ferguson Chapter I Section 2.6 Q 2 Q 3 In a game of Nim with piles (1,2,3,. . . , 63) nd a winning move. Q 4 A game of chomp begins with the following combination (
School: Berkeley
Course: Game Theory
Stat 155 Homework # 2 Due February 10 Problems: Q 1 Consider a 2 person rst price auction with reserve price r (in such an auction the highest bidder pays his bid and wins the item if it is greater than r while if neither bidder bids more than r then no o
School: Berkeley
Course: Game Theory
Stat 155 Homework # 1 Due February 3 Problems: Q 1 Let N be uniform on cfw_1, 2, . . . , 10 and let X be a binomial Bin(N, 1/2). Find the mean and variance of X. Q 2 Let X1 , X2 , X3 be independent Exp(1) random variables. Calculate the density and mean o
School: Berkeley
Course: Game Theory
Stat 155 Homework # 2 Due February 10 Problems: Q1 Solution (a) The P states are the even integers. 100 is a P position We can verify this by noting that, the terminal state is even, all move from N (odd) states move to P (even) states and all moves from
School: Berkeley
Course: Theory Of Probability
Statistics 116 - Fall 2004 Theory of Probability Assignment # 7 Due Friday, November 12 show (and briefly explain) all of your work Q. 1) (Ross # 6.2) Suppose that 3 balls are chosen without replacement from an urn consisting of 5 white and 8 red balls. L
School: Berkeley
Course: Theory Of Probability
Statistics 116 - Fall 2004 Theory of Probability Assignment # 4 Due Monday, October 25 show (and briefly explain) all of your work Q. 1) (Ross #3.60) A true-false question is to be posed to a husband and a wife team on a quiz show. Both the husband and th
School: Berkeley
Course: Introduction To Statistics
Stat 20 HW#8: Ch. 18 Review: 2, 4, 8, 10; Ch. 19 Review: 1, 4, 5, 6; Ch. 20 Review: 3, 4, 7, 8 Chapter 18 2. (a) The expected value is: 4*400 = 1600 Standard Error = sqrrt(400)*2.24 = 45 z = (1500 1600)/45 = -2.22 The probability equals about 99% (b) Redr
School: Berkeley
Course: Introduction To Statistics
Solution of HW set 10 Chapter 24 1. (a) The elevation is estimated as 81,411 inches. It is likely to be off by 6 inches or so. The estimation of the population is the average of the sample, which is 81,411 inches. The SE is SDbox/sqrt(n) = 30/sqrt(5) = 6
School: Berkeley
Stat 215B (Spring 2005): Lab 3 GSI: Victor Panaretos victor@stat.berkeley.edu Due March 8 at the Lab Section Part 1 : Simultaneous Inference In this section we revisit the data from the previous lab. Recall that the scenario involved the study of li
School: Berkeley
1 1 2 5 3&4 1 2&5 3 4 135 1 4 2 3&5 1 4&5 2 3 154 1&2 4&5 1&2&4 5 3 1&3 4 2&5 1&3&5 4 2 1&4 5 2&3 12 1254 1 2&5 3&4 1352 1425 1 4&5 2&3 1542 1&2 4&5 3 1&2&4&5 1&3 4 5 1&4 1&4 5 3 123 12543 1 2&5 4 13524 14253 1 4&5 3 15423 1&2 5 1&2&4&5 3 1&3 4 5 2 1&4 2
School: Berkeley
Course: Concepts Of Probability
Statistics 134, Section 2, Spring 2010 Instructor: Hank Ibser Lectures: TTh 11-12:30 in 60 Evans. Oce Hours: TTh 9:30-10:30 and 3:40-4:30, in 349 Evans Hall. Other times/places by appt. Oce Phone: 642-7495 Email: hank@stat.berkeley.edu Text: Probability b
School: Berkeley
Course: Introductory Probability And Statistics For Busines
UNIVERSITY OF CALIFORNIA Department of Economics Econ 100B Course Outline Spring 2012 Economics 100B Economic Analysis: Macroeconomics Professor Steven A. Wood Administrative Detail: Class Sessions: Tuesdays and Thursdays, 3:30 p.m. 5:00 p.m., 2050 Valley
School: Berkeley
Course: Introductory Probability And Statistics For Busines
Statistics 21, Section 1, Spring 2012 Instructor: Hank Ibser Lectures: MWF 9-10, 155 Dwinelle Email: hank@stat.berkeley.edu Office Hours: MW 10:10-11, 1:10-2, in 349 Evans Hall. Text: Statistics, 4rd ed. by Freedman, Pisani, Purves, Well cover most of cha
School: Berkeley
Course: Introductory Probability And Statistics For Busines
Schedule for Stat 21, Fall 2013 Note: Chapter readings are from FPP, and SG refers to Professor Philip Starks free online text SticiGui. notes by RP indicates Professor Roger Purves notes on chance variables, which will be posted on Canvas later. Week 1 (
School: Berkeley
Course: Introductory Probability And Statistics For Busines
STAT 21 Syllabus Course Information: Instructor: Shobhana Murali Stoyanov, shobhana@stat.berkeley.edu Class time: TuTh 2-3:30P, F295 Haas Office hours: W: 11-1P & by appointment, 325 Evans Text: Statistics, 4th ed., by Freedman, Pisani, and Purves. Supple
School: Berkeley
Statistics 21, Section 1, Spring 2010 Instructor: Hank Ibser Lectures: TTh 2-3:30pm, 2050 VLSB Email: hank@stat.berkeley.edu Oce Phone: 642-7495 Oce Hours: TuTh 9:30-10:30, 3:40-4:30, in 349 Evans Hall. Other times/places by appointment. Text: Statistics,
School: Berkeley
Course: Sampling Surveys
STAT152: Survey Sampling, Fall 2005 http:/www.stat.berkeley.edu/users/hhuang/STAT152.html Homework & lab assignment SYLLABUS Haiyan Huang, 317 Evans, (510)-642-6433 hhuang@stat.berkeley.edu Office Hours: M 4:00pm-5:00pm; T 3:00pm-4:00pm; or by appoi