# Final Study Guide

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.