AP Statistics

Dr. JonesPeriods 1 & 4

AP Stat Exam:Wednesday, May 13

Noon• 40 Multiple Choice, 90 minutes, 50% of score• 5 FRQ, 65 minutes, 37.5% of score• 1 Investigative Task, 25 minutes, 12.5% of

score• Calculators are expected.• Typically about 55 – 60% of students score 3

or better.

AP Preparation Materials

1. Your Textbook. Starnes, Yates, and Moore (2012). The Practice of Statistics, 4th Ed.

2. apcentral.collegeboard.com3. KhanAcademy.org3. AMSCO’s AP Statistics: Preparing for the

Advanced Placement Exam / Edition 2 by Bohan and Chance.

4. 5 Steps to a 5: AP Statistics by Duane C. Hinders5. Other materials are available online.

Main Topics & % of AP Exam

• Section 1: Exploring Data (Looking for and explaining trends and patterns in data – 20-30%)

• Section 2: Sampling and Experimentation (planning and conducting a study (10-15%)

• Section 3: Anticipating patterns (exploring random phenomena using probability and simulation – 20-30%)

• Section 4: Statistical Inference (estimating population parameters and hypothesis testing -- 30-40%)

Section 1: Exploring DataLooking for and explaining trends and patterns in data

• Exploring one variable data sets (center, spread)• Comparing one-variable distributions (graphs,

shape, center/spread, outliers, clusters, gaps)• Exploring two-variable data sets (linearity,

association, residuals, transformations)• Exploring categorical data (frequency tables, bar

charts, marginal frequencies, conditional frequencies, association)

Section 2: Sampling and Experimentation• Overview of data (methods of data collection—

census, survey, experiment, observation)• Planning and conducting a study (what counts as

data, how data will be analyzed, population vs sample, random selection, bias, sampling methods)

• Planning and conducting an experiment (what counts as data , how data will be analyzed, treatments, controls, bias, confounding, blinding, randomization)

• Generalizability and drawing conclusions.

Section 3: Anticipating patterns

• Probability. Concept of uncertainty, law of large numbers, independent, conditional, distributions, random variables

• Combining independent random variables. Descriptive stats for sums /differences of independent random variables

• Normal Distribution. Properties, tables, modeling with normal distribution

• Sampling Distributions. Sample proportion, sample mean, central limit thm, t-distribution, chi-square distribution

Section 4: Statistical Inference & Hypothesis Testing

• Point Estimation and confidence intervals. Population parameters and confidence intervals – proportions, difference between 2 proportions, means, difference between means, bias, variability, slope of regression line

• Tests of significance. Null and alternative hypotheses, Type 1 & Type 2 errors, power, tests for proportions, tests for mean, Chi-square test for goodness of fit, test for slope of least square regression line