STAT 205
Introduction to Mathematical Statistics
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Lectures
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Tentative Schedule
Lecture: Topic | Supplementary Material | Practice Problems | |
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1: Introduction to the instructor/course + Course Syllabus + Introduction to Data | Diez, Barr, and Çetinkaya-Rundel (2016) Section 1.2, 1.3 | Diez, Barr, and Çetinkaya-Rundel (2016): Exercises: 1.1, 1.9, 1.13, 1.15, 1.17, 1.27, 1.39, 1.43 | |
2: Summarizing Data | Diez, Barr, and Çetinkaya-Rundel (2016) Sections 2.1 and 2.2 (can skip special topics) |
Diez, Barr, and Çetinkaya-Rundel (2016) Exercises: 2.1, 2.5, 2.11, 2.13, 2.15, 2.17, 2.27, 2.33 JB exercises3 Ch 3 Exercises: 10, 20, 21, 22, 23, 31, 32, 34, 39, 36, 37, 39, 40, 41, 45, 46, 48, 49, 50 |
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34: Getting Started with Quarto: stat205demo (source qmd), cheer.csv | Wickham, Çetinkaya-Rundel, and Grolemund (2023) Chapter 28 Quarto tutorial Hello, Quarto |
Assignment 1 for practice with quarto. Wickham, Çetinkaya-Rundel, and Grolemund (2023) 28.3.1: 1, 2, 3; 28.5.5: 1, 2; 28.6.3: 1, 2, 3 |
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4: Sampling Distributions | ⚬ Ross - Ch 6; Balka 4.1, 4.2, 4.3, 4.4, 4.5 ⚬ What is the CLT Video ⚬ StatKey: Sampling Distribution for a Mean ⚬ Khan: Sampling Distribution for proportions |
JB exercises5 Ch 7: 1, 6, 7, 8, 9, 10, 11, 12, 13, 19, 20, 21, 24, 25 | |
5: Likelihood and Parameter Estimation | (Ramachandran and Tsokos 2020) - Ch 5.1-5.3; Ross - Ch 6 | JB exercises (solutions found here) Ch 7: 14, 15 Rice (2007) Section 8.10: 4, 5, 6, 7 (excluding part |
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4b: Examples with Sampling Distributions | Sampling Distributions in Action | See exercises for lecture 4 | |
6: Confidence Intervals for Means and Proportions | (Illowsky and Dean 2022) - Ch 8 (Balka n.d.) Ch 5 (Ramachandran and Tsokos 2020) Ch 5.4-5.5 |
JB exercises Ch 8:
CI for \(p\): Diez, Barr, and Çetinkaya-Rundel (2016) Ch 6: 6.1, 6.5, 6.7, 6.9, 6.10, 6.11, 6.13, 6.15 |
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7: Hypothesis Testing for one-sample mean (critical value approach) | Devore, Berk, and Carlton (2021) 9.1, | ||
8: Hypothesis Testing for one-sample proportions (\(p\) -value approach) | Devore, Berk, and Carlton (2021) 9.4, Diez, Barr, and Çetinkaya-Rundel (2016) 5.3 | ||
Midterm 1 | Practice Problems and Suggested Problems | ||
9: \(t\) tests and CI for one-sample mean (\(\sigma\) unknown) | Diez, Barr, and Çetinkaya-Rundel (2016) Chapter 6 and 7, Balka (n.d.) Section 9.10 | ||
Inference for difference of Two Means | Balka (n.d.) chapter 10, Diez, Barr, and Çetinkaya-Rundel (2016) 7.2, 7.3 | ||
Examples involving two-sample \(t\)-tests | |||
Analysis of Variance (ANOVA) | Lesson 10 Penn Stat 500, Chapter 14 Balka (n.d.) | ||
Chi-squared test for one-sample variance | Balka (n.d.) 12.1 – 12.3 (Ramachandran and Tsokos 2020) 4.2 | ||
Contingency Table Analysis | Balka (n.d.) Chapter 13, Penn Stat STAT 500 Lesson 8, Diez, Barr, and Çetinkaya-Rundel (2016) 6.3, 6.4 | ||
Sampling from a Finite Population | Casella and Berger (2002) 5.1, Rice (2007) 7.3 | ||
Properties of Parameter Estimators | Devore, Berk, and Carlton (2021) 7.3, 7.4 | ||
18: Linear Regression and Correlation | |||
Post Midterm Review | See the list of learning outcomes coded by importance here and suggested practice problems here |
References
Footnotes
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