Download AP Statistics Overview

AP Statistics
Dr. Jones
Periods 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.com
3. KhanAcademy.org
3. 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. Hinders
5. 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 -- 3040%)
Section 1: Exploring Data
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Looking 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