This post contains a study guide for the Final. It outlines the “critical concepts” – i.e. the things you need to know for the exam. It also lists practice questions for each of the assigned chapters from Freedman.

## Readings and Practice Questions

You should read the assigned chapters (listed below) and complete the practice questions (listed below). Answers to practice questions are in back of book.

- Chapter 1 – NA
- Chapter 2 – Question 7 page 22
- Chapter 3 – Question 1 page 46
- Chapter 4 – Question 8 page 71, Question 4 page 73
- Chapter 5 – Question 1 page 88, Question 1 page 89
- Chapter 6 – Just read! No questions
- Chapter 8 – Questions 2 + 3 Page 134
- Chapter 9 – Question 2 page 152
- Chapter 10 -Question 2 page 167
- Chapter 11 -Question 1-2 page 197; Question 3 page 189; Question 3 page 193
- Chapter 12 – read!
- Chapter 16 – Question 1 + 2 page 277
- Chapter 17 – Question 3 page 303
- Chapter 18 – Question 2 page 319
- Chapter 19 – Question 11 page 350
- Chapter 20 – Question 2 page 366
- Chapter 21 – Question 5 page 380, Question 6 page 387
- Chapter 23 – Question 9 page 414, Question 5 page 420, Question 2 page 425
- Chapter 26 – Question 5 page 478, Question 4 page 481, Question 7 + 10 page 487
- Chapter 27 – Question 4 + 5 page 515

## Critical concepts

- Spatial Autocorrelation (from lecture)
- Weights matrix
- Scale and correlations, MAUP.

- Regression
- When it works and when it doesn’t
- Slope and intercept
- Residuals what they are, what their patterns should be.
- RMS of the Residuals
- Geographic patterns in residuals (from lecture)
- Deriving the coefficient of determination (r-squared, from lecture)
- Making predictions with a regression model.

- Simpsons Paradox.
- Controlled Experiments
- Observational Studies
- Confounding
- Average (concept + formula)
- Standard Deviation (concept + formula)
- Normal curve, understand its properties and the kinds of processes that generate it.
- Chance Error
- Bias (be able to contrast with chance error)
- The difference between population parameters and statistics
- Standard Error
- Contrast with SD
- Compute SE for mean, sum, and percent (formula)

- Tests of significance (hypothesis tests)
- One sample T-Test (formula + concept)
- Two sample T-Test (formula + concept)
- What’s the difference between z and t test?
- Correlation (concept + formula)
- Confidence Intervals and how they relate to the normal curve.