Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
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 • • • • 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