Course Overview
This course provides a first introduction to statistical thinking and data analysis, taught in English. Students learn to collect, summarize, and interpret data using probability theory, descriptive statistics, and foundational inferential methods.
Learning Objectives
- Understand fundamental theories and principles of statistics.
- Acquire statistical analysis techniques for scientific problem-solving and optimal decision-making.
- Develop the ability to analyze and interpret data using statistical software (R).
Topics Covered
Ch. 1 Introduction to data · Ch. 2 Summarizing data · Ch. 3 Probability · Ch. 4 Distributions of random variables · Ch. 5 Foundations for inference · Ch. 6 Inference for categorical data · Ch. 7 Inference for numerical data · Ch. 8 Introduction to linear regression
Teaching Method
Lecture 80% · Review 10% · Q&A 10%. Lectures use PPT slides and board writing. Online sessions via Zoom when necessary.
Textbook
Diez et al., OpenIntro Statistics, 4th ed. (OpenIntro, Inc., 2019) — free PDF
Prerequisites
Calculus.
Course Schedule
All sessions are 75 minutes. Quiz = in-class written quiz.
| Wk | Date | Topic | |
|---|---|---|---|
| 1 | Mar 3 (Tue) | Ch. 1 & 2 — Introduction & Summarizing Data Presenting numerical / categorical data | |
| 1 | Mar 5 (Thu) | Ch. 3 — Probability Conditional probability, Bayes' Theorem | |
| 2 | Mar 10 (Tue) | Ch. 3 — Probability (cont.) Random variables, expectation, variance | |
| 2 | Mar 12 (Thu) | Ch. 3 — Probability (cont.) Joint pdf, independence, covariance, correlation | |
| 3 | Mar 17 (Tue) | Ch. 4 — Distributions of Random Variables Uniform distribution, Normal distribution | |
| 3 | Mar 19 (Thu) | Quiz 1 | Quiz 1 |
| 4 | Mar 24 (Tue) | Ch. 4 — Distributions (cont.) Bernoulli distribution, Binomial distribution | |
| 4 | Mar 26 (Thu) | Ch. 5 — Foundations for Inference Point estimates and sampling variability, Central Limit Theorem | |
| 5 | Mar 31 (Tue) | Ch. 5 — Foundations for Inference (cont.) Confidence intervals for a proportion | |
| 5 | Apr 2 (Thu) | Ch. 5-2 — Special Topic 1 Sampling distribution · Make-up class Apr 3 | |
| 6 | Apr 7 (Tue) | Quiz 2 | Quiz 2 |
| 6 | Apr 9 (Thu) | Ch. 5-2 — Special Topic 2 Point estimation · Make-up class Apr 10 | |
| 7 | Apr 14 (Tue) | Ch. 7 — Inference for Numerical Data One-sample means with t-distribution, Paired data | |
| 7 | Apr 16 (Thu) | Summary & Review | |
| 8 | Apr 21–23 | Midterm Exam Coverage: Ch. 1–5, 7 (partial) | Midterm |
| 9 | Apr 28 (Tue) | Ch. 7 — Inference for Numerical Data (cont.) Hypothesis test for population mean | |
| 9 | Apr 30 (Thu) | Ch. 7 — Inference for Numerical Data (cont.) Difference of two means (1) | |
| 10 | May 5 (Tue) | Children's Day Make-up class held Mar 27 | No Class |
| 10 | May 7 (Thu) | Cadet Day | No Class |
| 11 | May 12 (Tue) | High School Visit (Admissions Outreach) | No Class |
| 11 | May 14 (Thu) | High School Visit (Admissions Outreach) | No Class |
| 12 | May 19 (Tue) | Quiz 3 | Quiz 3 |
| 12 | May 21 (Thu) | Ch. 7 — Inference for Numerical Data (cont.) Difference of two means (2) | |
| 13 | May 26 (Tue) | Ch. 7 — Inference for Numerical Data (cont.) Power calculations for a difference of means | |
| 13 | May 28 (Thu) | Ch. 8 — Introduction to Linear Regression Fitting a line, residuals, and correlation (1) | |
| 14 | Jun 2 (Tue) | Ch. 8 — Linear Regression (cont.) Fitting a line, residuals, and correlation (2) | |
| 14 | Jun 4 (Thu) | Quiz 4 | Quiz 4 |
| 15 | Jun 9 (Tue) | Ch. 8 — Linear Regression (cont.) Least squares regression | |
| 15 | Jun 11 (Thu) | Ch. 8 — Linear Regression (cont.) Inference for linear regression | |
| 16 | Jun 16–18 | Final Exam Coverage: Comprehensive | Final |
| 17 | Jun 23–25 | National March (Cross-Country Trek) | No Class |
Lecture Notes
| Chapter | Files |
|---|---|
Ch. 1 — Introduction to Data | Slides |
Ch. 2 — Summarizing Data | Slides Annotated |
Ch. 3 — Probability | Slides Annotated |
Ch. 4 — Distributions of Random Variables | Slides Annotated |
Ch. 5-1 — Foundations for Inference | Slides Annotated |
Ch. 5-2 — Special Topics Sampling distribution, Point estimation | Slides Annotated |
Ch. 6 — Inference for Categorical Data | Slides |
Ch. 7 — Inference for Numerical Data | Slides Annotated |
Ch. 8 — Introduction to Linear Regression | Slides Annotated |
Ch. 9 — Multiple and Logistic Regression | Slides |
Quiz & Exam
2026 Spring
| Item | Date | Files |
|---|---|---|
Quiz 1 Ch. 3–4 (Distributions) |
Mar 19 | ProblemSolution |
Past Exams — 2025 Spring
| Item | Files |
|---|---|
Quiz 1 |
ProblemSolution |
Quiz 2 |
ProblemSolution |
Midterm Exam |
ProblemSolution |
Quiz 3 |
ProblemSolution |
Quiz 4 |
ProblemSolution |
Final Exam |
ProblemSolution |
Past Exams — 2025 Fall
| Item | Files |
|---|---|
Quiz 1 |
ProblemSolution |
Quiz 2 |
ProblemSolution |
Midterm Exam |
ProblemSolution |
Quiz 3 |
ProblemSolution |
Quiz 4 |
ProblemSolution |
Final Exam |
ProblemSolution |
