Probability

CDFs 1

CDFs 2

CDFs 3

Expectation and Variance for Continuous RVs

Uniform Density

Uniform cdf

Expectation and Variance of Uniform

Moment Generating Function for Uniform

Normal pdf and cdf

z-scores or standardized variables

Standard Normals and Percentiles

MGF for Standard Normal

Exponential pdf cdf and Memoryless Property

Gamma pdf and Gamma Function

Gamma Mean, Variance; Chi Squared

Beta Distribution

More on the Beta Function

Expectations of Functions of Random Variables

MGFs and Gamma Example

Mean and Variance of Gamma

General Real-Valued RVs

General Real-Valued RVs - Example Part 1

General Real-Valued RVs - Example Part 2

General Real-Valued RVs - Example Part 3

Multivariate Discrete

Multivariate Discrete Example Part 1

Multivariate Discrete Example Part 2

Multivariate Continuous Part 1

Multivariate Continuous Part 2

Multivariate Continuous Example

Marginal Distributions 1

Marginal Distributions 2

Marginal Distributions 3

Marginal Distributions 4

Marginal Distributions 5

Conditional Distributions 1

Conditional Distributions 2

Conditional Distributions 3

Conditional Distributions 4

Independent Random Variables 1

Independent Random Variables 2

Independent Random Variables 3

Expectation of Functions of RVs 1

Expectation of Functions of RVs 2

Expectation of Functions of RVs 3

Covariance 1

Covariance 2

Covariance 3

Covariance 4

Covariance 5

E and Var of Linear Functions of RVs 1

E and Var of Linear Functions of RVs 2

Multinomial Distribution 1

Multinomial Distribution 2

Conditional Expectation 1

Conditional Expectation 2

Conditional Expectation 3

Exam 2

Covers all videos since Exam 1, and essentially chapters 4 and 5 of the text.

Here is a review guide.

Method of Distribution Functions 1

Method of Distribution Functions 2

Method of Distribution Functions 3

Method of Transformations 1

Method of Transformations 2

Moment Generating Function Methods 1

Moment Generating Function Methods 2

Moment Generating Function Methods 3

Moment Generating Function Methods 4

Moment Generating Function Methods 5

Moment Generating Function Methods 6

Order Statistics 1

Order Statistics 2

Order Statistics 3

Sums of Normals and Sample Variance 1

Sums of Normals and Sample Variance 2

Sums of Normals and Sample Variance 3

Sums of Normals and Sample Variance 4

Sums of Normals and Sample Variance 5

Central Limit Theorem 1

Central Limit Theorem 2

Central Limit Theorem 3

Exam 3

Covers all videos since Exam 2, and essentially chapters 6 and 7 of the text. Here is a review guide.

Quiz Dates

Aug. 25- Section 2.3: Set Notation

Aug. 27 - Sections 2.4 & 2.5: Basic Probability

Aug. 29 - Section 2.6: Counting

Sept. 1 - No Class! Labor Day Holiday

Sept. 3 - Section 2.7: Conditional Prob. & Independence

Sept. 5 - Section 2.10: Total Probability and Bayes's Rule

Sept. 8 - Expectation and Variance

Sept. 10 - Binomial Random Variables

Sept. 12 - Geometric Random Variables

Sept. 15 - Negative Binomial and Hypergeometric

Sept. 17 - Poisson

Sept. 19 - Moment Generating Functions and Chebyshev's Ineq.

Sept. 22 - Continuous Variables

Sept. 24 - Expectation for Continuous Variables

Sept. 26 - Exam I (covers Chapters 3 and 4)

Sept. 29 - Uniform Random Variables

Oct. 1 - Normal Random Variables

Oct. 3 - Gamma & Exponential

Oct. 6 - Beta

Oct. 8 - Moment Generating Functs. & Chebyshev's Ineq.

Oct. 10 - Mixed Probability Distributions

Oct. 13 - FALL BREAK!

Oct. 15 - Multivariate Distributions 1

Oct. 17 - Multivariate Distributions 2

Oct. 20 - Marginal and Conditional Distributions

Oct. 22 - Independent Random Variables

Oct. 24 - Expectation of Functions of RVs

Oct. 27 - Covariance

Oct. 29 - Expectation and Variance of Linear Funcs. of RVs

Oct. 31 - Multinomial

Nov. 3 - Conditional Expectation

Nov. 5 - Functions of RVs: Method of Dist. Functions

Nov. 7 - Exam II

Nov. 10 - Method of Transformations

Nov. 12 - Moment Generating Function Methods 1

Nov. 14 - Moment Generating Function Methods 2

Nov. 17 - Order Statistics

Nov. 19 - Behavior of Sums of Normals

Nov. 21 - Behavior of Sample Variance

Nov. 24 - Central Limit Theorem

Nov. 26 - Thanksgiving Break!

Nov. 28 - Thanksgiving Break!

Dec. 1 - Exam III

Dec. 3 - Final Exam Review and Last Day of Classes

Old Exams

Exam I Fall 2010

Solutions

Exam II Fall 2010

Solutions

Exam II Fall 2011

Solutions

Exam III Fall 2011

Solutions

Homework & Due Dates

Summer 2019 class: you should plan to take your exams according to this rough schedule:

Exam I: around Friday, June 21.

Covers sections 2.3 through 3.11 (scroll down and look to the left... you'll see where the Exam 1 videos end and the Exam II videos begin)

Exam II: around Friday, July 12.

Covers sections 4.2 through 5.11.

Exam III: around Friday, August 2.

Covers sections 6.3 through 7.3.

Final Exam: around Friday, August 9. Cumulative.

Email your professor to arrange times and dates for your exams.

For Summer 2019 class: please ignore the homework due dates below. However, these are the homework problems you should work. Homework will not be collected, but it is strongly suggested you do these problems.

Aug. 27- Section 2.3, #s 4, 5, 6, 7

Aug. 29 - Sections 2.4 and 2.5, #s 11, 14, 15, 18, 21, 22, 23, 27, 29, 33

Sept. 3 - Section 2.6, #s 35, 36, 41, 43, 46, 47, 51, 53, 57, 58, 68, 69

Sept. 5 - Section 2.7, #s 71, 75, 77, 81, 83. Section 2.8, #s 84, 86, 89, 97, 99, 104

Sept. 8- Section 2.9, #s 114, 115, 119, 120, 121, Section 2.10, #s 128, 132, 135, 137

Sept. 10 - Section 3.2, #s 2, 4, 6, 10, Section 3.3, #s 19, 23, 27, 29, 32, 33

Sept. 12 - Section 3.4, #s 40, 44, 48, 51, 56, 57, 65

Sept. 15 - Section 3.5, #s 66, 67, 70, 72, 77, 80, 85

Sept. 17 - Section 3.6, #s 90, 91, 93, 94, 97, Section 3.7, #s 102, 105, 110

Sept. 19 - Section 3.8, #s 122, 130, 134, 138, 141,

Sept. 22 - Section 3.9, #s 147, 148, 150, 151, 153, 159, 160, Section 3.11, #s 167, 168

Sept. 24 - Exam I Review - Also, Section 4.2, #s 8, 9, 15, 17, Section 4.3, #s 21, 25, 26, 32, 34, 35

Sept. 26 - Exam I (covers Chapters 2 and 3)

Sept. 29 - No homework due!

Oct. 1 - Section 4.4, #s 39, 41, 42, 43, 45, 50,

Oct. 3 - Section 4.5, #s 58, 59, 61, 62, 71, 75

Oct. 6 - Section 4.6, #s 81, 82, 89, 92, 94, 95, 104, 109, 112

and the following:

1. The times between arrivals to the YMCA are independent exponential random variables with mean 3 minutes.

(a) What is the probability that the time between the 4th and 5th customers exceeds 5 minutes?

(b) Given the 4th customer arrived 10 minutes ago, what is the probability that the time from now until the next arrival exceeds 5 minutes?

(c) Given the 4th customer arrived 10 minutes ago, what is the expected time from now until the next arrival?

(d) The 6th customer just arrived. What is the distribution of time until the 11th customer arrives, and what is the expected amount of time until this happens?

2. Prove that the geometric random variable has the memoryless property (in fact, it's the only discrete rv. that does, but you don't have to prove uniqueness).

Oct. 8 - Section 4.7, #s 124, 125, 128, 130

Oct. 10 - Section 3.9, #158, Section 4. 9, # 137, 139, 140, 141, 143, 144, 145, Section 4.10, #s 146, 149

Oct. 13 - No classes. Fall break!

Oct. 15 - Section 4.11, #s 155, 156, 157, 159

Oct. 17 - HA! No homework due.

Oct. 20 - Section 5.2, #s 7, 9, 11, 15, 17

Oct. 22 - Section 5.3, #s 19, 23, 25, 34, 36

Oct. 24 - Section 5.4, #s 43, 45, 48, 57, 61, 64, 70, 71

Oct. 27 - Sections 5.5 and 5.6, #s 75, 77, 79, 81

Oct. 29 - Section 5.7, #s 89, 91, 93, 94, 96, 98

Oct. 31 - Section 5.8, #s 103, 105, 107, 108, 110

Nov. 3 - Section 5.9, #s 119, 123, 124, 126

Nov. 5 - Exam II Review. Also, Section 5.11, #s 133, 136, 139, 140, 142

Nov. 7 - Exam II (covers Chapters 4 and 5).

Nov. 10 - Section 6.3, #s 1, 3, 7, 8, 14, 22

Nov. 12 - Section 6.4, #s 23, 28, 29, 30

Nov. 14 - No Homework Due! But the next one is long!

Nov. 17 - Section 6.5, #s 37, 38, 40, 41, 42, 43, 49, 52, 54, 57, and the following: Suppose X is distributed geometric(p). How does the random variable pX/lambda behave as p goes to 0? Here, lambda is a constant. Hint: Use moment generating functions.

Nov. 19 - Section 6.7, #s 72, 74, 76, 81

Nov. 21 - No homework due!

Nov. 24 - Exam III Review. Section 7.2, #s 11, 12, 14, 15, 20, 21, 33, 34, 35

Nov. 26 - No classes- Thanksgiving break.

Nov. 28 - No classes - Thanksgiving break.

Dec. 1 - Exam III (covers Chapters 6 and 7). Also, Section 7.3, #s 43, 44, 46, 47, 52, and the following:

The average and standard deviation of railroad cars and their contents are 8,000 lbs and 1,000 lbs, respectively. Fifty of these cars are to be loaded onto a barge. What is the approximate chance that the total weight exceeds the load capacity of the barge of 425,000 lbs?

Dec. 3 - Final Exam Review. Final exam is cumulative.

Dec. 5 - Final Exam. 8:00 am - 10:00 am.