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Lecture TopicReadingHomework (to submit)Extra ProblemsLogistics
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2023-08-29Unit 1: Probability Basics
Course introduction, set theory		3.1, 3.2, 3.3Ch 3: 1-3, 7Read the course website at https://tjo.is/teaching/probstat-fa23/
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2023-08-31Axioms of probability3.4
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2023-09-05Sampling3.5Ch 3: 10, 12-14, 18
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2023-09-07Conditional probability, Bayes rule, independence3.6, 3.7, 3.8Ch 3: 21, 23, 25, 26, 29, 34, 35, 37
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2023-09-12Unit 2: Random Variables
Discrete random variables, continuous random variables		4.1, 4.2Ch 4: 2-4, 6, 8, 9Unit 1 homework due for completion (before class);
Unit 1 solutions out (after class)
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2023-09-14Jointly distributed random variables4.3Ch 4: 10, 12-14, 16, 17, 19
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2023-09-19Expected value, variance4.4, 4.5, 4.6Ch 4: 24-28, 31, 32, 39-43
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2023-09-21Covariance, Chebyshev's inequality4.7, 4.9Ch 4: 44, 45
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2023-09-26Unit 3: Probability Distributions
Discrete distributions, continuous distributions		5.1, 5.2, 5.3, 5.4, 5.6, 5.7Ch 5: 2, 5, 6, 12, 18, 37Ch 5: 1, 3, 8, 11, 17, 21, 22, 38, 45Unit 2 homework due for completion (before class);
Unit 2 solutions out (after class)
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2023-09-28Normal(μ,σ) and associated distributions5.5, 5.8Ch 5: 24, 25, 28, 31, 32, 36Ch 5: 23, 27, 33, 47
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2023-10-03Lecture catch-up, Exam 1 reviewUnit 3 homework due for completion (before class);
Unit 3 solutions out (after class)
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2023-10-05Midterm Exam 1 on Units 1, 2, 3 (in class)
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2023-10-10No class (Monday schedule)
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2023-10-12Unit 4: Statistics Basics
Sample mean, central limit theorem		6.1, 6.2, 6.3Ch 5: 34, 35;
Ch 6: 6, 9, 10, 12, 13		Ch 5: 26;
Ch 6: 2, 3, 5, 7, 8, 11, 14, 15
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2023-10-17Confidence intervals, sample variance (online -- no in-person class)6.4, 6.5Ch 6: 18, 19Lecture recording and exit question on Blackboard; exit question due by end-of-day
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2023-10-19No class
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2023-10-24Unit 5: Parameter Estimation
Point estimation		7.2Ch 7: 1Ch 7: 2, 3Unit 4 homework due for completion (before class);
Unit 4 solutions out (after class)
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2023-10-26Interval estimation: Normal(μ,σ)7.3Ch 7: 8-10, 20, 22Ch. 7: 11-15, 18, 23, 27, 28
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2023-10-31Interval estimation: difference of means, Bernoulli(θ)7.4, 7.5Ch 7: 41-43, 49, 55Ch 7: 44, 50, 52-54Come to class in costume if you want!
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2023-11-02Unit 6: Hypothesis Testing
Hypothesis testing basics		8.1, 8.2Ch 8: 1
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2023-11-07Tests involving Normal(μ,σ)8.3Ch 8: 4-6, 9, 12Ch 8: 11Unit 5 homework due for completion (before class);
Unit 5 solutions out (after class)
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2023-11-09Tests involving Normal(μ,σ) -- t tests
(online -- no in-person class)		8.3Ch 8: 13, 17, 23, 25, 26Ch 8: 20, 21Lecture recording and exit question on Blackboard; exit question due by end-of-day
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2023-11-14Goodness-of-fit tests11.2Ch 11: 1, 2Ch 11: 6, 10
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2023-11-16Lecture catch-up, Exam 2 reviewUnit 6 homework due for completion (before class);
Unit 6 solutions out (after class)
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2023-11-21No class (campus closed)
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2023-11-28Midterm Exam 2 on Units 4, 5, 6 (in class)
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2023-11-30Unit 7: Statistical Computing
R tutorial		2.8, 5.10See "Unit 7 Homework, Part 1" on BlackboardAttempt any of the previous problems involving Z-score transformation, the central limit theorem, t-tests, or goodness of fit tests, except this time use R.Try out R at https://webr.r-wasm.org/latest/; Bring computers to class (if possible)
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2023-12-05Least-squares regression, correlation coefficient9.1, 9.2, 9.5Ch 9: 1-5;
Show R code used to solve all problems		Ch 9: 6, 7Bring computers to class (if possible)
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2023-12-07Lecture catch-up, final exam reviewUnit 7 homework due for completion (before class);
Unit 7 solutions out (after class);
Bring computers to class (if possible)
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2023-12-19Final Exam (take home)Final exam posted 3:15p;
Final exam due 6:00p
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Course schedule subject to change.