1 / 10

AP Statistics

This comprehensive guide outlines the major topics covered in the first semester of AP Statistics, including shapes of distributions, measures of center, normal distributions, regression, collecting data, basic probability, discrete random variables, and distribution of sample statistics.

edwardrose
Download Presentation

AP Statistics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. AP Statistics Major Topics first semester by chapter

  2. The dirty details • 3rd period takes it on Friday!! • The final is 50 multiple choice questions. • The final will replace your lowest test grade if higher. • The final counts 20% for everyone. (that is about 3 test grades) • You get the same green formula sheet that you have your unit tests. • Each chapter is represented fairly evenly, so expect about 6-8 questions per chapter. • Major topics per chapter are on the slides that follow • Advice: do a little everyday, use review guide to help you, feel free to come look at old tests if you want.

  3. Breakdown by chapter • Chapter One: Shapes of distributions and measures of Center: 6 questions • Chapter 2: Normal distributions: 10 Questions • Chapter 3: Regression: 8 Questions • Chapter 4: Collecting Data: 10 questions • Chapter 5: Basic Probability: 4 questions • Chapter 6: Discrete Random Variables: 10 Questions • Chapter 7: Distribution of sample statistics and CLT: 2 Questions

  4. Chapter 4: Collecting Data • Ways to collect data • SRS • Stratified Random Sample • Systematic Sample • Cluster Sample • Ways to sample badly • Idea of Bias • Observation vs Experiment (stratified vs blocking) • Placebo Effect • Blind vs. Double blind • When can we make decisions about results?

  5. Chapter One: Intro to Data • Categorical vs Quantitative Data • Different types of graphs and what they show • Shapes of distributions • Describing Distributions (SOCCS) • Numerical centers and spreads of distributions • Mean • Median • Mode • Range • Variance • Standard Deviation • 5 number summary • How skewed Data and outliers effect the above.

  6. Chapter 2: Modeling Data • Percentiles • Z-scores and how to interpret • Effects of Transformations on data. (adding or multiplying data by a constant) • Normal Distributions • Empirical Rule • The “standard Normal Distribution” • Using Z-scores and normal table • Calculator commands (normalcdf and invnorm) • Assessing Normality with the normal plot.

  7. Chapter 3: Regression • Explanatory vs Response Variable • DFS: Direction, Form and Strength of a Distribution. • Calculating the Least Square Regression Line • Interpreting Slope and y-intercept • Making predictions with y-hat, when you can • Outliers vs influential points. • Interpreting r and r-squared. • Interpreting Residuals

  8. Chapter 5: Probability(Everyone’s Favorite) • What probability is trying to tell us? • Sample Space • Rules for Probability • Independent and disjoint (mutually exclusive) • AND & OR (what to do) • Conditional Probability • Simulations

  9. Chapter 6: Probability Distributions • Discrete vs continuous random variables • What makes a legitimate probability distribution • Expected Value of a probability distribution • Standard deviation of a probability distribution • Is a game fair? • Binomial vs. Geometric random variable; how do you check • Mean and standard deviation of a binomial random variable • Calculator syntax.

  10. Chapter Seven: Sampling Distributions • Parameters vs. Statistics • How x-bar and p-hat behave • Precision vs accuracy • Normal Calculations • What happens if data is not normal? CLT • When can you treat distribution of p-hat as a normal distribution • As sample size goes up what happens to summary statistics, particularly standard deviation?

More Related