# Semester II Study Guide - AP Statistics

## Seniors: Tuesday May 21, 2019

You are required to bring your own TI-84, pencil and eraser. It is a good idea to have a spare set of 4-AAA batteries with you in case your calculator needs it during the test.

Quarter Exams represent 20% of your grade (10% each). There will be 4 free response questions (10 min each), and 20 multiple choice questions (2-3 min each). They will be based on the Free Response questions you had on May 16, 2019. Here are some helpful links:

You are provided a Formula Sheet that also has tables for the Normal, T, and Chi-Square distributions.

The College Board that administers the AP exam has this helpful passage about what should be included in a free response question:

Show all your work. Indicate clearly the methods you use, because you will be scored on the correctness of your methods as well as on the accuracy and completeness of your results and explanations.

Here is a check list of some major topics from the first few chapters:

• Chapter 1: Individuals, Categorical and Quatitive variables, distribution, center, spread, normal distribution, geometric distribution, histogram, stem plots, time plot, box plot symetric skewed outlier center spread and shape of a distribution, 5 number summary, mean, standard deviation, median, Q1, Q3, IQR (2016-1, 2015-1, 2013-6 2012-3a)
• Chapter 2: Density Curves and the Normal Distribution Inflection Points, percentile, z-score, transforming data, 68-95-99.7 Rule, Standard Normal N[0,1], z-scores (again), Calculations, Assessing Normality of a Distribution. (2009-2, 2013-3, 2011-1)
• Chapter 3: Scatterplots, Correlation, Regression Line (LSRL), r, r2, Residuals, Residual Plots, , Std Dev of the residual, Influential Observations, Lurking Variables (2016-6, 2015-5, 2014-6)
• Chapter 4: Experimental Units, confounding, random assignment and selection, double-blinding, block design, placebo effect, scope of inference, informed consent, confidentiality. (2016-3, 2015-6, 2014-4, 2013-2, 2011-3)
• Chapter 5: Randomness, Probability and Simulation, Probability, Law of Large Numbers, Sample Space, Probability Model, Conditional Probability, Independence.
• Chapter 6: Discrete Random Variables, Continuous Random Variables, Probability Distribution, mean (expected value) of a random variable, variance and std dev of a random variable, Linear Transformations (360, 361, 362), mean and variance of sum of random variables (365, 367), mean and variance of difference of random variables (371), Independent random variable definition (365), Binomial Setting (383), Binomial formulas (387, 388, 391), Sampling without replacement condition (394), Normal Approximation for Binomial (395), Geometric Setting (397), Geometric Formulas (399, 401).
• Chapter 7: Parameter vs Statistic, Sampling Variability, Sampling Distribution vs Population Distribution, Unbiased Estimator (421), Why n-1? (423), Bias vs Variability of a Statistic(425ff),Mean and Std Dev of a sample proportion (436), Mean and Std Deviation of a Sample Mean (444), Sample mean from a Normal Population (447), Central Limit Theorem (Sample mean from even Non-Normally distributed distributions)-(450-451)
• Chapter 8: Estimating with confidence, Confidence interval Estimating proportions and mean, t-distribution, SE
• Chapter 9: Significance tests Summary (p 545), Tests about a Population Proportion Summary (p.561), Tests about a Population Mean Summary (p 586)
• Chapter 10: Estimating and Testing the Difference of Two Proportions (p. 620), the Difference of Two Population Means (p. 650)
• Chapter 11: Chi Square Test for Goodness of Fit (p. 685) and Inference for 2-way tables including Tests for homogeneity ,tests for Independence (page 718-719), and Follow-Up Analysis (p. 709)
• Chapter 12: Inference for Linear Regression (p. 758), including knowing the "LINER" Conditions For Regression Inference (741-743), Regression Standard Error, s (745), Standard Error of the slope, SEb (746), t-interval for estimating the actual Slope (747), the t-Test for Slope(751), and Transformations to Achieve Linearity (p. 785)
• Chapter 13: Comparing Two Population Parameters: Comparing Two Means, Comparing Two Proportions, Confidence Intervals (p. 810), and Hypothesis Tests (pp. 813-815)
• Chapter 14:Chi Square: Test for Goodness of Fit (p. 840), Null and Alternative Hypotheses for Chi-Square GOF (846), Follow-Up Analysis (p. 845), Chi-Square for Two-Way Tables (p. 876), Null and Alternative hypothese for Chi-Square Two-Way Tables (p. 853), Computing Expected Table (872), Chi Square Statistic Definition (869).
• Observational Studies topics including: The evil "Convenience Sample", The Statistical four-letter-word: bias, The wicked "Voluntary response Sample," The Golden "SRS" ( the vaccine against bias), The use of the random digit table, Stratified Random sample, Cluster Sample, the bane of undercoverage and nonresponse (221-2) and the loathsome "Wording Bias"
• Experimental Design topics including Lurking Variables and Confounding, Treatment Experimental Units and Subjects, Random Assignment (rather than selection), Completely Randomized Design, Control, Random Assignment and Replication, Double Blind and Statistical Significance, Blocking, Matched Pairs Design.

Review your work and note what you did well, correct your mistakes, and practice the topics you feel you haven't mastered.