Topics, Exams and Homework Assignments

Week Dates Topics Sections Covered Homework Due
1Aug 24—Aug 28 Probability in the World Around Us. Randomness with known and unknown structure. Introduction to R. 1.1, 1.2, 1.3, 1.4, 1.5, 2.1, 2.22.2: 2.5, 2.7, 2.9, 2.13
R:  R1
Sep 2
2Aug 31—Sep 4 Sample Spaces and Events. 2.32.3: 2.17, 2.19, 2.21, 2.23Sep 9
3Sep 7Labor Day - no class.
R (Posted):  R2
Sep 30
3Sep 9—Sep 11 More on sets, sample spaces, events. Inclusion-Exclusion Principle for 2 sets and 3 sets (Example 2.2). 2.2, 2.3
Inclusion-Exclusion for 2/3 sets:  Solve Example 2.2 and practice on similar problems.
Sep 16
4Sep 14—Sep 18 Definition of Probability. Counting Rules Used in Probability. 2.4, 2.52.4: 2.35, 2.37, 2.45, 2.48, 2.51, 2.53, 2.61, 2.5: 2.67, 2.69, 2.71Sep 21
5Sep 21Counting rules. Multi-stage processes. Two-way tables. Probability trees. Review for Midterm 1.2.4, 2.5
R (Reminder):  R2
Sep 30
5Sep 23 TAKE-HOME MIDTERM 1 POSTED. Counting Rules. Permutations, Combinations. Distinct vs. identical items. 2.4, 2.5
5Sep 25 Counting Rules used in Probability. Review of Take-Home Midterm 1 topics. Assignment R2.
6Oct 6 NOTE: This syllabus item is added purely to describe R Assignment 3. The topics in this assignment cover: counting rules, conditional probability, Bayes Formula, computing contingency tables with R, computing multinomial coefficients. First encounter of the multi-nomial distribution. 2.4, 3.1, 3.2, 3.3
R (Posted):  R3
Oct 21
6Sep 28—Oct 3 Conditional Probability. Independence. Theorem on Total Probability and Bayes Rule. 3.1, 3.2, 3.33.1: 3.5, 3.13, 3.15, 3.2: 3.27, 3.35, 3.37Oct 7
7Oct 5—Oct 9 Theorem on Total Probability and Bayes Rule. 3.33.3: 3.43, 3.45, 3.48, 3.49Oct 14
8Oct 12—Oct 16 Random Variables and Their Probability Distributions. 4.14.1: 4.1, 4.7, 4.8, 4.9, 4.12Oct 21
9Oct 19Review for Midterm 2.
9Oct 21Midterm 2.
9Oct 23 Random Variables and Their Probability Distributions. The Bernoulli Distribution. The Binomial Distribution. 4.1, 4.2, 4.34.2: 4.19, 4.23, 4.41
R (Posted):  R4
Oct 28
10Oct 26—Oct 30 Independence of Random Variables. Distribution of a sum of independent random variables. Convolution of probability functions. Expected Value of Discrete Random Variables. Variance. 4.4, 4.5, 4.64.4: 4.43, 4.49, 4.51, 4.61, 4.63, 4.6: 4.67, 4.72, 4.73, 4.78, 4.79Nov 4
11Nov 2—Nov 6 Tchebysheff's Inequality. The Geometric Distribution. The Negative Binomial Distribution. The Poisson Distribution. The Hypergeometric Distribution. 4.7, 4.8, 4.9, 4.104.7: 4.89, 4.101, 4.8: 4.109, 4.110, 4.9: 4.125, 4.126, 4.127, 4.128, 4.132, 4.135, 4.10: 4.139, 4.143
R (Due):  R4
Nov 11
12Nov 9—Nov 13 The Moment-Generating Function. The Probabilty-Generating Function.
12Nov 11 Veteran's Day - no class.
12  The Moment-Generating Function. The Probabilty-Generating Function. 4.11, 4.12
13Nov 23—Nov 27 Continuous random Variables and Their Probability Distributions. 5.1, 5.2
14Nov 30Review for Midterm 3. Expected Values of Continuous Random Variables. The Uniform Distribution. The Exponential Distribution. 5.3, 5.4
14Dec 2Midterm 3.
14Dec 4 The Gamma Distribution. The Normal Distribution. 5.5, 5.65.4: 5.41, 5.42, 5.43, 5.5: 5.65, 5.67, 5.6: 5.83, 5.85
R (Due):  R5
Dec 9
15Dec 7—Dec 9 Expectation of Discontinuous functions and Mixed Probability Distributions. Review before the Final Exam.
Finals WeekDec 15 (Tuesday)Final Exam, 10:30 am - 12:30 pm (regular room).