This section includes assigned readings from the three main texts used in the course.
Larsen and Marx's book is a bit more chatty than Ross', while DeGroot and Schervish's is a very good book but somewhat more difficult. You can find additional resources in the related resources section.
Readings are from Ross [ROS], Larsen and Marx [LM], and DeGroot and Schervish [DS]. Note that ROS does not cover all the topics but more closely follows the material taught in class.
|1||Set and Probability Theory||Chapter 3||Chapters 1.1–1.3, 2.1–2.10||Chapters 1, 2.1–2.3|
|2||Random Variables, Probability Mass/Density Function, Cumulative Distribution Function (Univariate Model)||Chapters 4.1–4.2, 5.1, pp. 160-1||Chapter 3.1–3.4||Chapter 3.1–3.3|
|3||Multiple Random Variables, Bivariate Distribution, Marginal Distribution, Conditional Distribution, Independence, Multivariate Distribution (Multivariate Model)||Chapter 4.3||Chapter 3.5–3.6, 3.9||Chapter 3.4–3.7|
|4||Expectation (Moments)||Chapter 4.4–4.9||Chapter 3.10–3.13, 3.15–3.16||Chapter 4.1–4.7|
|5||Review for Exam 1|
|6||Random Variable and Random Vector Transformations (Univariate and Multivariate Models)||Chapter 3.7||Chapter 3.8–3.9|
|7||Special Distributions (Discrete and Continuous)||Chapter 5.1–5.8||Chapters 3.3, 4.1–4.3, 4.5–4.6||Chapter 5.1–5.6, 5.9|
|8||Review for Exam 2|
|9||Random Sample, Law of Large Numbers, Central Limit Theorem||Chapters 6, 4.9, 1, 2||Chapters 3.14, pp. 272-5, 5.1, 5.4||Chapters 4.8, 5.7, 7.1, 7.7|
|10||Point Estimators and Point Estimation Methods||Chapter 7.7 and 7.1–7.2||Chapter 5.2||Chapter 6.5–6.6|
|11||Interval Estimation and Confidence Intervals||Chapters 7.3–7.6, 5.8.2–5.8.3||Chapter 5.3||Chapter 7.5|
|12||Hypothesis Testing||Chapter 8||Chapters 6, 9.1–9.2||Chapter 8|
|13||Review for Exam 3|
Advanced topics, time permitting: Bayesian Analysis and Nonparamatric Methods.