1How to use this book¶
This is the Fall 2026 coordinator companion edition of the MATH 2200 coursebook. The chapters are exactly the same as the standard edition — this edition simply adds the Weekly Reading Map below so that, in any of the six coordinated sections, you always know what to read before each class.
Read a little ahead of your section, in order:
Before each week’s first class, skim that week’s chapter(s) in the table below — the intuition first, then the worked examples.
Read with R open. Every worked example is meant to be run, not just read.
Do the worked examples before the practice problems. Each new skill is demonstrated once, start to finish, before you are asked to use it.
Use the appendices (formula sheet, distribution tables, R quick reference, the which-test decision guide, glossary, and odd-numbered answers) whenever you get stuck.
If you want the full narrative on who the book is for and how each concept is taught, read the Welcome page first.
2A note on two different chapter numbers¶
Your textbook reading is keyed to two numbering systems, and it helps to keep them straight:
This book’s chapters (
ch01–ch13) are the ones you read here.OpenIntro Statistics, 4th edition section numbers (for example, “2.1”) are the matching reading in the free OpenIntro textbook, which the master syllabus follows.
They are not the same numbers. In particular, your in-class quizzes are numbered by the OpenIntro chapter (the pacing calendar’s “Quiz 5 (Ch 5)” means OpenIntro Chapter 5), and one OpenIntro chapter can span several chapters in this book. The table below lines the two systems up week by week so you never have to guess.
3Weekly Reading Map — Fall 2026¶
The table maps each week of the Fall 2026 semester to the chapter(s) to read in this book, the matching OpenIntro 4th section(s), the week’s focus, and the graded events tied to that week. Dates cover both the MoWe and TuTh section patterns; confirm your own section’s exact meeting days against the master pacing calendar.
| Week (dates) | Read in this book | OpenIntro 4th | This week’s focus | Graded events |
|---|---|---|---|---|
| 1 (Aug 24–27) | Chapter 1 (§1.1–1.2) | 1.1–1.2 | Data, variables, study design | Lab 1; HW1 assigned |
| 2 (Aug 31–Sep 3) | Chapter 1 (§1.3–1.4); start Chapter 2 | 1.3–1.4, 2.1 | Sampling, experiments; numerical data | HW1 due |
| 3 (Sep 8–10) | Chapter 2 | 2.1 | Center, spread, boxplots | Quiz 1 (OpenIntro Ch 1); Lab 2 |
| 4 (Sep 14–17) | Chapter 3; start Chapter 4 | 2.2, 3.1–3.2 | Categorical data; probability, conditional | Quiz 2 (OpenIntro Ch 2) |
| 5 (Sep 21–24) | Chapter 4; Chapter 5 | 3.4–3.5, 4.1 | Random variables; the Normal model | Quiz 3 (OpenIntro Ch 3); Lab 3; Project 1 proposal due |
| 6 (Sep 28–Oct 1) | Review Ch 1–5; start Chapter 6 | (review), 5.1–5.2 | Exam 1; foundations for inference | ★ Exam 1 (OpenIntro Ch 1–4) |
| 7 (Oct 5–8) | Chapter 6; Chapter 7; Chapter 8 | 5.2–5.3 | Confidence intervals; hypothesis-test logic | Quiz 4 (OpenIntro Ch 4) |
| 8 (Oct 12–15) | Chapter 9 | 6.1–6.2 | Inference for one & two proportions | Quiz 5 (OpenIntro Ch 5); Lab 4; Project 1 write-up due |
| 9 (Oct 19–22) | Chapter 11; start Chapter 10 | 6.3–6.4, 7.1 | Chi-square; one-sample mean (t) | Quiz 6 (OpenIntro Ch 6) |
| 10 (Oct 26–29) | Chapter 10 | 7.2, 7.3 | Paired & two-sample means | Lab 5 |
| 11 (Nov 2–5) | Chapter 12 | 7.5 | Comparing many means (ANOVA) | Quiz 7 (OpenIntro Ch 7); Lab 6 |
| 12 (Nov 9–12) | Start Chapter 13 | 8.1 | Scatter, correlation, fitting a line | — |
| 13 (Nov 16–19) | Chapter 13 | 8.2, 8.4 | Least squares; inference for the slope | Quiz 8 (OpenIntro Ch 8); Lab 7 |
| 14 (Nov 23–24) | Review Ch 5–13 | (review) | Exam 2 | ★ Exam 2 (OpenIntro Ch 5–8); Project 2 proposal due |
| 15 (Nov 30–Dec 3) | Course synthesis (no new chapter) | 9.1–9.2 (intro) | Multiple-regression preview; synthesis | Project 2 write-up + presentation |
| 16 (Dec 7–8) | Final review — no new reading | — | Comprehensive final review | ★ Final exam (Dec 9–15) |
4How the book’s chapters line up with OpenIntro¶
If you prefer to think chapter-by-chapter instead of week-by-week, this is the full crosswalk between the two numbering systems.
| This book | OpenIntro 4th |
|---|---|
| Chapter 1 — Data & Study Design | 1.1–1.4 |
| Chapter 2 — Summarizing Numerical Data | 2.1 |
| Chapter 3 — Summarizing Categorical Data & Tables | 2.2 |
| Chapter 4 — Probability Foundations | 3.1–3.3 |
| Chapter 5 — Random Variables & the Normal Model | 3.4–3.5, 4.1 |
| Chapter 6 — Sampling Distributions & the CLT | 5.1 |
| Chapter 7 — Confidence Intervals | 5.2 |
| Chapter 8 — Hypothesis Testing Logic | 5.3 |
| Chapter 9 — Inference for Proportions | 6.1–6.2 |
| Chapter 10 — Inference for Means | 7.1–7.3 |
| Chapter 11 — Chi-Square Methods | 6.3–6.4 |
| Chapter 12 — ANOVA | 7.5 |
| Chapter 13 — Correlation & Linear Regression | 8.1–8.4 |
One thing to notice: the course does not read this book straight through. Chi-square (Chapter 11) is taught in Week 9, before you finish the means chapter (Chapter 10), because the master syllabus folds the chi-square test in around inference so it can appear on Exam 2. The Weekly Reading Map above always shows the correct order for your section — follow it, not the chapter numbers.