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STA 4321 - Intro To Probability - University Of Florida Study Resources
  • 34 Pages ISM_chapter4
    ISM_chapter4

    School: University Of Florida

    Course: INTRO TO PROBABILITY

    Chapter 4: Continuous Variables and Their Probability Distributions y <1 0 .4 1 y < 2 a. F ( y ) = P(Y y ) = .7 2 y < 3 .9 3 y < 4 1 y4 1.0 F(y) 0.0 0 0.2 0.4 0.6 0.8 4.1 1 2 y 3 4 5 b. The graph is above. 4.2 a. p(1) = .2, p(2) = (1/

  • 30 Pages ISM_chapter10
    ISM_chapter10

    School: University Of Florida

    Course: INTRO TO PROBABILITY

    Chapter 10: Hypothesis Testing 10.1 10.2 See Definition 10.1. Note that Y is binomial with parameters n = 20 and p. a. If the experimenter concludes that less than 80% of insomniacs respond to the drug when actually the drug induces sleep in 80% of i

  • 44 Pages annual97
    Annual97

    School: University Of Florida

    Course: Introduction To Probability

    Annual Report March 16, 1996 - March 15, 1997 Department of Statistics University of Florida Gainesville, FL 32611-8545 June, 1997 Contents 1 Research Activities: March 16, 1996 - March 15, 1997 7 2 Non-Refereed Publications 13 3 Technical Reports 16 4 Gr

  • 28 Pages ISM_chapter3
    ISM_chapter3

    School: University Of Florida

    Course: INTRO TO PROBABILITY

    Chapter 3: Discrete Random Variables and Their Probability Distributions 3.1 3.2 P(Y = 0) = P(no impurities) = .2, P(Y = 1) = P(exactly one impurity) = .7, P(Y = 2) = .1. We know that P(HH) = P(TT) = P(HT) = P(TH) = 0.25. So, P(Y = -1) = .5, P(Y = 1)

  • 15 Pages ISM_chapter7
    ISM_chapter7

    School: University Of Florida

    Course: INTRO TO PROBABILITY

    Chapter 7: Sampling Distributions and the Central Limit Theorem 7.1 a. c. Answers vary. d. The histogram exhibits a mound shape. The sample mean should be close to 3.5 = e. The standard deviation should be close to / 3 = 1.708/ 3 = .9860. f. Very s

  • 5 Pages hwk7
    Hwk7

    School: University Of Florida

    Solutions to Homework 7 5.140 For gamma distribution with parameters and , the moment generating function is M (t ) etx 0 1 x 1e x / dx ( ) 1 ( ) 0 x 1 x /( e 1 t ) dx ( ) 1 t ( ) 1 t 6.1 a. Let Z denote the number of contracts assigned to firm

  • 5 Pages ltrnotes10
    Ltrnotes10

    School: University Of Florida

  • 5 Pages hwk4
    Hwk4

    School: University Of Florida

    4.51 a. each individual has the probability of 0.5 to pass the gene to an offspring. P ( the child has no disease gene) P (the first person do not pass gene to the child) P (the second person do not pass gene to the child) 0.5 0.5 0.25 b. for each chil

  • 3 Pages ltrnotes11
    Ltrnotes11

    School: University Of Florida

  • 6 Pages ltrnotes12
    Ltrnotes12

    School: University Of Florida

  • 6 Pages ltrnotes13
    Ltrnotes13

    School: University Of Florida

  • 4 Pages ltrnotes14
    Ltrnotes14

    School: University Of Florida

  • 2 Pages Homework3_sol
    Homework3_sol

    School: University Of Florida

  • 5 Pages ltrnotes15
    Ltrnotes15

    School: University Of Florida

  • 4 Pages lecture9
    Lecture9

    School: University Of Florida

  • 3 Pages lecture8
    Lecture8

    School: University Of Florida

  • 4 Pages lecture7
    Lecture7

    School: University Of Florida

  • 9 Pages hwk8
    Hwk8

    School: University Of Florida

  • 5 Pages hwk6
    Hwk6

    School: University Of Florida

    Solutions to Homework 6 5.63 Solve equation 0.5 F m 1 e m We get m ln 2 0.693 5.65 Let X denote the daily rainfall during a randomly selected September day. a. E X 8, b. 1 V X 2 160 1 0.75 , then we have k 2 . From Tchebysheffs Theorem, k2 1 P ( X 2 )

  • 10 Pages hwk9
    Hwk9

    School: University Of Florida

  • 5 Pages lecture 2
    Lecture 2

    School: University Of Florida

  • 4 Pages lecture3
    Lecture3

    School: University Of Florida

  • 5 Pages lecture4
    Lecture4

    School: University Of Florida

  • 4 Pages lecture5
    Lecture5

    School: University Of Florida

  • 4 Pages hwk5
    Hwk5

    School: University Of Florida

    Solutions to Homework 5 5.5 a. 0 0 f x dx ce x /10 dx 10 ce x /10 thus c 10c 1 1 . 10 b. if b 0, F (b) 0 , if b 0, then F (b) b b 1 x /10 e dx e x /10 1 e b /10 0 0 10 f ( x)dx b thus 1 e b /10 , F (b) 0, b0 b0 c. P ( X 15) 1 P( X 15) 1 P( X 15) 1

  • 4 Pages lecture6
    Lecture6

    School: University Of Florida

  • 8 Pages ltrnotes16
    Ltrnotes16

    School: University Of Florida

  • 1 Page quiz1solns
    Quiz1solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

  • 2 Pages quiz9solns
    Quiz9solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

    STA 4321/5325 - Spring 2010 Quiz 9 - April 16 Name: There are ve problems in this quiz. Each problem has exactly one correct answer. Problem 1 Let X and Y be independent random variables with E (X ) = 2, E (Y ) = 1, V (X ) = 16, and V (Y ) = 3. Then (a) E

  • 5 Pages sampleexam3solns
    Sampleexam3solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

    STA 4321/5325 - Spring 2010 Sample Exam 3 Note: This is an example adapted from previous STA 4321/5325 exams. It is intended to be of approximately the same length and style as the actual exam. However, it is NOT guaranteed to match the content or coverag

  • 6 Pages sampleexam4solns
    Sampleexam4solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

    STA 4321/5325 - Spring 2010 Sample Exam 4 Note: This is an example adapted from previous STA 4321/5325 exams. It is intended to be of approximately the same length and style as the actual exam. However, it is NOT guaranteed to match the content or coverag

  • 10 Pages samplefinalexamsolns
    Samplefinalexamsolns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

  • 4 Pages Sample Space, Events, and Probability
    Sample Space, Events, And Probability

    School: University Of Florida

    Course: Intro To Probability Theory

    Lecture 2 Agenda 1. Sample Spaces and Events 2. Probability Sample Spaces and Events Whenever we perform any experiment it can result in several dierent outcomes. But before we perform the experiment we cant exactly say which outcome will occur. Denition

  • 3 Pages Probability, counting, and permutations
    Probability, Counting, And Permutations

    School: University Of Florida

    Course: Intro To Probability Theory

    Lecture 3 Agenda 1. One more example to understand the formal denition of probability 2. Fundamental principles of counting 3. Evaluating probabilities using permutations Example Experiment: There are 3 mail boxes. Three people come one after another, and

  • 4 Pages More counting
    More Counting

    School: University Of Florida

    Course: Intro To Probability Theory

    Lecture 4 Agenda 1. Some more counting rules 2. And the related examples Remember the following two results from previous lecture. Lemma 1. Total number of ways of selecing r objects from n objects where - order of selection is important & - the same obje

  • 5 Pages Conditional Probability, Total Probability, and Bayes Rule
    Conditional Probability, Total Probability, And Bayes Rule

    School: University Of Florida

    Course: Intro To Probability Theory

    Lecture 5 Agenda 1. Conditional Probability 2. Theorem of Total probability 3. Bayes Rule Conditional Probability Suppose you are going to have a surgery, but before that you want to talk to a Doctor about how likely it is that the surgery will be a succe

  • 2 Pages quiz8solns
    Quiz8solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

  • 2 Pages quiz7solns
    Quiz7solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

  • 2 Pages quiz6solns
    Quiz6solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

  • 2 Pages syllabus
    Syllabus

    School: University Of Florida

    STA 4321/5325 Introduction to Probability/Fundamentals of Probability Section 1192 & 6790 Spring 2012 Course Information and Policies Objectives: The sequence of courses STA 4321-4322 (rep. 5325-5328) provides a formal and systematic introduction to mathe

  • 5 Pages exam1solns
    Exam1solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

    STA 4321/5325 - Spring 2010 Exam 1 February 3, 2010 Full Name: KEY On my honor, I have neither given nor received unauthorized aid on this examination. Signature: This is a 50 minute exam. There are 4 problems, worth a total of 40 points. You may use on

  • 8 Pages exam3solns
    Exam3solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

    STA 4321/5325 - Spring 2010 Exam 3 March 29, 2010 Full Name: KEY On my honor, I have neither given nor received unauthorized aid on this examination. Signature: This is a 50 minute exam. There are 4 problems, worth a total of 40 points. You may use one

  • 5 Pages exam4solns
    Exam4solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

    STA 4321/5325 - Spring 2010 Exam 4 April 19, 2010 Full Name: KEY On my honor, I have neither given nor received unauthorized aid on this examination. Signature: This is a 50 minute exam. There are 4 problems, worth a total of 40 points. You may use one

  • 2 Pages quiz2solns
    Quiz2solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

  • 2 Pages quiz3solns
    Quiz3solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

  • 2 Pages quiz4solns
    Quiz4solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

  • 2 Pages quiz5solns
    Quiz5solns

    School: University Of Florida

    Course: Introduction To Probability / Fundamentals Of Probability

  • 3 Pages Independence
    Independence

    School: University Of Florida

    Course: Intro To Probability Theory

    Lecture 6 Agenda 1. Independence Independence In our everyday lives when we see two things which are not inuenced by one another, we call them independent of each other. For example how many sandwitches you will eat today and whether the Gators are gonna

  • 4 Pages Homework2_sol
    Homework2_sol

    School: University Of Florida

  • 2 Pages STA4321icexam2
    STA4321icexam2

    School: University Of Florida

    Course: Introduction To Probability

    STA 4321/5325 Fall 2010 Exam 2 Full Name: On my honor, I have neither given nor received unauthorized aid on this examination. Signature: This is a 50 minute exam. There are 4 problems, worth a total of 40 points. Remember to show your work. Answers lacki

  • 2 Pages Syllabus4321-5325Fall06
    Syllabus4321-5325Fall06

    School: University Of Florida

    Course: Introduction To Probability

    Fundamentals of Probability STA 4321 (Section 4529) and STAT 5325 (Section 5566) Fall, 2006 Objective: This course is a broad introduction to the mathematical theory of probability. The objective of the course is to introduce the student to probability as

  • 2 Pages Syllabus4322
    Syllabus4322

    School: University Of Florida

    Course: Introduction To Probability

    STA4322 (Sect 5238) Introduction to Statistical Theory STA5328 (Sect 4048)Fundamentals of Statistical Theory Summer B 2009 Instructor: Mark C. Yang Office: 202 Griffin-Floyd Hall Phone: 273-2979 E-mail: yang@stat.ufl.edu Office Hours: 5:10pm-6:30pm Tuesda

  • 3 Pages courseinfo
    Courseinfo

    School: University Of Florida

    STA 4321/5325 Introduction to Probability / Fundamentals of Probability Section 7461/7490 (3 credit hours) Spring 2012 Course Information and Policies Objectives: The sequence of courses STA 4321-4322 (rep. 5325-5328) provides a formal and systematic intr

  • 1 Page STA4321grdcutoffs
    STA4321grdcutoffs

    School: University Of Florida

    These are tentative grade cutoffs, which may be slightly modified later. A = 90 or above A- = 86-89 B+ = 81-85 B = 71-80 B- = 66-70 C+ =61-65 C = 56-60 C- =51-55 D+ =46-50 D = 41-45 D- = 36-40 E = 35 or below

  • 7 Pages STA4321ln2
    STA4321ln2

    School: University Of Florida

  • 6 Pages STA4321ln3
    STA4321ln3

    School: University Of Florida

  • 6 Pages STA4321ln4
    STA4321ln4

    School: University Of Florida

  • 6 Pages STA4321ln5
    STA4321ln5

    School: University Of Florida

  • 2 Pages Syllabus4321-5325Fall05
    Syllabus4321-5325Fall05

    School: University Of Florida

    Course: Introduction To Probability

    Fundamentals of Probability STA 4321 (Section 4529) and STAT 5325 (Section 5566) Fall, 2005 Objective: This course is a broad introduction to the mathematical theory of probability. The objective of the course is to introduce the student to probability as

  • 32 Pages Homework1_sol
    Homework1_sol

    School: University Of Florida

    Course: Introduction To Probability

    STA 4321 Solution to Homework 1 2.10 a. Because the two jobs are indentical, the order is not important in this problem. The sample space is S = cfw_J, D, cfw_J, M , cfw_J, S , cfw_J, N , cfw_D, M , cfw_D, S , cfw_D, N , cfw_M, S , cfw_M, N , cfw_S, N . E

  • 2 Pages STA4321HW4
    STA4321HW4

    School: University Of Florida

    Course: Introduction To Probability

    STA 4321 Introduction to Probability Theory Assignment 4 Assigned Monday March 15 Due Monday March 22 Show your work to receive full credit. 1. A machine for lling cereal boxes has a standard deviation of 1 ounce in ll per box. Assume that the ounces of l

  • 2 Pages STA4321icexam2-SPRING10
    STA4321icexam2-SPRING10

    School: University Of Florida

    Course: Introduction To Probability

    STA 4321/5325 Spring 2010 Exam 2 Full Name: On my honor, I have neither given nor received unauthorized aid on this examination. Signature: This is a 50 minute exam. There are 4 problems, worth a total of 40 points. Remember to show your work. Answers lac

  • 3 Pages Exam1sta4321
    Exam1sta4321

    School: University Of Florida

    Course: Introduction To Probability

    STA4321 Name: Practice Exam 1 UFID: Show your work to receive full credit. A formula sheet is provided on the last page. I promise not to cheat on this exam. I understand that accessing notes programmed into my calculator constitutes cheating. I also pr

  • 3 Pages exam3-smpl-f99
    Exam3-smpl-f99

    School: University Of Florida

    Course: Introduction To Probability

    Sample Problems for Exam 3 STA 4321 Mathematical Statistics I Fall 1999 These questions are only meant as a study aid and to help you test your knowledge. Being able to solve them does not guarantee that you are well-prepared for the exam. 1. For each of

  • 2 Pages quiz1
    Quiz1

    School: University Of Florida

    Course: Introduction To Probability

  • 2 Pages quiz2
    Quiz2

    School: University Of Florida

    Course: Introduction To Probability

  • 2 Pages STA4321 HW3(2)
    STA4321 HW3(2)

    School: University Of Florida

    Course: Introduction To Probability

    STA 4321 Introduction to Probability Theory Assignment 3 Assigned Friday February 12 Due Monday February 22 Show your work to receive full credit. 1. A study is to be conducted in a hospital to determine the attitudes of nurses toward various administrati

  • 2 Pages STA4321HW1
    STA4321HW1

    School: University Of Florida

    Course: Introduction To Probability

    STA 4321 Introduction to Probability Theory Assignment 1 Assigned Wednesday January 13 Due Wednesday January 20 Show your work to receive full credit. 1. Let A1 , A2 , . . . be a countable collection of sets. Give a formal proof (not a picture) of the fol

  • 2 Pages STA4321HW2
    STA4321HW2

    School: University Of Florida

    Course: Introduction To Probability

    STA 4321 Introduction to Probability Theory Assignment 2 Assigned Wednesday January 20 Due Monday January 25 Show your work to receive full credit. 1. Students attending the University of Florida can select from 130 major areas of study. A students major

  • 6 Pages STA4321ln6
    STA4321ln6

    School: University Of Florida

  • 5 Pages STA4321ln7
    STA4321ln7

    School: University Of Florida

  • 6 Pages STA4321ln8
    STA4321ln8

    School: University Of Florida

  • 2 Pages quiz7
    Quiz7

    School: University Of Florida

  • 2 Pages quiz9
    Quiz9

    School: University Of Florida

  • 2 Pages STA4321samplequiz5
    STA4321samplequiz5

    School: University Of Florida

  • 5 Pages hwk1
    Hwk1

    School: University Of Florida

    Solutions to Homework 1 2.10 a. The two jobs are identical, so the order does not matter when selecting two applicants, the sample space is S cfw_ Jim, Don , Jim, Mary , Jim, Sue , Jim, Nancy , Don, Mary , Don, Sue , Don, Nancy , Mary, Sue , Mary, Nancy

  • 7 Pages hwk2
    Hwk2

    School: University Of Florida

    Solutions to Homework 2 2.41 10 There are ways to choose 4 engineers out of 10, a nd there are 4! ways to assign 4 4 different positions to 4 engineers chosen, thus 10 There are 4! 5040 ways can the director fill the positions. 4 2.50 For each of the 10

  • 12 Pages hwk3
    Hwk3

    School: University Of Florida

    4.5 We need to assume each outcome is equally likely for each person to choose each door. Each person has four choices, thus there are 43 64 possible outcomes for three 3 people to enter the building. If x people choose door I, there are ways to specify

  • 22 Pages Correction for homework 2
    Correction For Homework 2

    School: University Of Florida

    Correction for e of 2.60 : The correct answer should be P (straight) = 10 (45 4) 52 5 which is the same as Prof. Han said in class. My answer to b of 2.60 is correct. There indeed 9 ways to select a straight ush in a specic suit, for 10, J, Q, K, ace in o

  • 1 Page explanations and correction to homework 3
    Explanations And Correction To Homework 3

    School: University Of Florida

    Explanation to 3.17 It seems that there are two dierent understandings on eldest daughters. If eldest daughter include the only daughter in the family, the answer is 0.75. The sample space is cfw_B11 B12, B21, B22, G11, G12, G21, G22. B or G denote the ge

  • 2 Pages quiz3
    Quiz3

    School: University Of Florida

  • 6 Pages exam4solution-SPRING12
    Exam4solution-SPRING12

    School: University Of Florida

  • 6 Pages exam3
    Exam3

    School: University Of Florida

  • 6 Pages STA4321ln9
    STA4321ln9

    School: University Of Florida

  • 7 Pages smplexmstncts
    Smplexmstncts

    School: University Of Florida

  • 7 Pages smplexmstnjtn
    Smplexmstnjtn

    School: University Of Florida

  • 3 Pages exam1solution-SPRING12
    Exam1solution-SPRING12

    School: University Of Florida

  • 3 Pages smlexamstn
    Smlexamstn

    School: University Of Florida

  • 2 Pages STA4321samplequiz3
    STA4321samplequiz3

    School: University Of Florida

  • 4 Pages exam2
    Exam2

    School: University Of Florida

  • 5 Pages exam2solutionSPRING10
    Exam2solutionSPRING10

    School: University Of Florida

  • 3 Pages Homework1_sol
    Homework1_sol

    School: University Of Florida

    STA 4321 Solution to Homework 1 2.10 a. Because the two jobs are indentical, the order is not important in this problem. The sample space is S = cfw_J, D, cfw_J, M , cfw_J, S , cfw_J, N , cfw_D, M , cfw_D, S , cfw_D, N , cfw_M, S , cfw_M, N , cfw_S, N . E

  • 6 Pages Inclusion Exclusion Principle, Random Variable, and Discrete Random Variable
    Inclusion Exclusion Principle, Random Variable, And Discrete Random Variable

    School: University Of Florida

    Course: Intro To Probability Theory

    Lecture 7 Agenda 1. Inclusion Exclusion Principle 2. Random Variable 3. Discrete Random Variable Inclusion Exclusion Principle Theorem 1. If A1 , A2 , . . . , Ak are k events, then k P (A1 A2 . . . Ak ) = P (Ai ) P (Ai1 Ai2 ) + 1i1 <i2 n i=1 (k1) . . . .

  • 7 Pages lecture2
    Lecture2

    School: University Of Florida

    Course: Introduction To Probability

    STA 4321 Kshitij Khare Spring 2013

  • 10 Pages lecture4 (1)
    Lecture4 (1)

    School: University Of Florida

    Course: INTRO TO PROBABILITY

    Lecture 4 Zhihua (Sophia) Su University of Florida Jan 21, 2015 STA 4321/5325 Introduction to Probability 1 Agenda Conditional Probability Independence Reading assignment: Chapter 2: 2.7 STA 4321/5325 Introduction to Probability 2 Conditional Probability

  • 10 Pages lecture5
    Lecture5

    School: University Of Florida

    Course: INTRO TO PROBABILITY

    Lecture 5 Zhihua (Sophia) Su University of Florida Jan 23, 2015 STA 4321/5325 Introduction to Probability 1 Agenda Inclusion-Exclusion Principle Theorem of Total Probability Bayes Rule Reading assignment: Chapter 2: 2.8, 2.9, 2.10 STA 4321/5325 Introducti

  • 9 Pages lecture6
    Lecture6

    School: University Of Florida

    Course: INTRO TO PROBABILITY

    Lecture 6 Zhihua (Sophia) Su University of Florida Jan 21, 2015 STA 4321/5325 Introduction to Probability 1 Agenda Random Variables Probability Mass Function Probability Distribution Function Reading assignment: Chapter 2: 2.11-2.13, Chapter 3: 3.1-3.2 ST

  • 9 Pages lecture7 (1)
    Lecture7 (1)

    School: University Of Florida

    Course: INTRO TO PROBABILITY

    Lecture 7 Zhihua (Sophia) Su University of Florida Jan 23, 2015 STA 4321/5325 Introduction to Probability 1 Agenda Properties of distribution function STA 4321/5325 Introduction to Probability 2 Properties of distribution function Let us recollect that if

  • 6 Pages lecture7_supp
    Lecture7_supp

    School: University Of Florida

    Course: INTRO TO PROBABILITY

    Lecture 7 Supplement Zhihua (Sophia) Su University of Florida Jan 23, 2015 STA 4321/5325 Introduction to Probability 1 Agenda Some results STA 4321/5325 Introduction to Probability 2 Some results These results will be used when we introduce families of di

  • 13 Pages lecture8
    Lecture8

    School: University Of Florida

    Course: INTRO TO PROBABILITY

    Lecture 8 Zhihua (Sophia) Su University of Florida Jan 26, 2015 STA 4321/5325 Introduction to Probability 1 Agenda Expected Values Variance Properties of Expected Values and Variance Reading assignment: Chapter 3: 3.3, 3.11 STA 4321/5325 Introduction to P

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