advertisement

Radnor High School Course Syllabus AP Statistics 0470 I. Course Description AP Statistics introduces students to the major concepts and tools for collecting, analyzing and drawing conclusions from data and exposes them to four broad concepts: exploring data for patterns and departures from patterns, sampling and experimentation in planning and conducting a study, anticipating patterns while exploring random phenomena using probability and simulation, and statistical inference - estimating population parameters and testing hypotheses. Students who successfully complete this course and the College Board AP Statistics examination may receive advanced credit for one semester of introductory college statistics. A graphing calculator is required. II. Materials & Equipment Introduction to the Practice of Statistics, Third Edition, Moore and McCabe – W.H. Freeman and Co. TI-83, TI-83 Plus or TI-84 Plus graphing calculator Minitab statistical software (available in two computer labs) Video series: Statistics – Decisions Through Data (25 fifteen minutes videos covering specific topics within the course) Supplemental video series Against All Odds: Inside Statistics, The Annenberg/CPB Collection, housed in the RHS library III. Course Goals & Objectives Prepare students to take the AP Statistics examination. Introduce students to technological methods of data analysis. Develop the students’ ability to collect, summarize, analyze and communicate their ideas through projects and data investigations. Conclude a solution process with a summary of results and evaluate the degree to which the results obtained represent an acceptable response to the initial problem and why the reasoning is valid. IV. Course Topics (Summary Outline) A. UNIVARIATE DATA Describing Distributions with Graphs Graphs for categorical variables – bar charts, pie charts, Pareto graphs Examining distributions – stemplots, histograms, timeplots Beyond the basics – decomposing time series Describing Distributions with Numbers Measures of center – the mean and the median Measures of spread – standard deviation; the quartiles, interquartile range, five number summary and boxplots Choosing the correct measure of center and spread; linear transformations Revised: March 10, 2016 The Normal Distribution The 68-95-99.7 rule (The Empirical Rule) The standard normal distribution; the area under the curve using Z scores Normal quantile plots; using normality to check for outliers B. BIVARIATE DATA Scatterplots; Correlation Interpreting scatterplots; adding categorical variables to scatterplots Correlation coefficient, r; properties of the correlation coefficient Least Squares Regression Fitting a line to data; least square regression; interpreting the regression line; prediction Correlation and regression; r2 Residuals Residuals; regression diagnostics; lurking variables; outliers and influential observations G. ONE AND TWO SAMPLE TESTING; SMALL AND LARGE SAMPLES The Student T Distribution The t distributions; degrees of freedom; sample standard deviation; robustness of the t distribution One sample t confidence interval One sample t test; matched pair Comparison of Two Means Two sample z confidence interval and test statistics for large samples Two sample t confidence intervals and test statistics for small samples Exponential Growth and Logarithmic Transformations The logarithm transformation; the use of residuals; prediction in the exponential growth model H. INFERENCE FOR PROPORTIONS Inference for One and Two Proportions Confidence Intervals and significance tests for one and two proportion Z tests Confidence intervals provide additional information Choosing a sample size Sampling Distribution of a Sample Mean Mean and standard deviation of X bar Sampling distribution of X bar The Central Limit Theorem I. CHI SQUARE Goodness of Fit The chi square distribution; degrees of freedom Significance testing for goodness of fit F. INTRODUCTION TO INFERENCE Confidence Intervals Confidence interval for a population mean How confidence intervals behave Choosing the sample size Tests of Significance, Large Sample Hypothesis testing; stating hypotheses, test statistics, p-values, statistical significance Tests for a population mean Two sided versus one sided tests and confidence intervals P-values versus fixed alpha values; alpha error (Type I error) Homogeneity and Independence Significance testing for independence using matrices; p-value, statistical significance The chi-square test and the z test J. INFERENCE FOR REGRESSION* Simple Linear Regression* Statistical model for linear regression Estimating the regression parameters Confidence intervals and significance tests Power and the Beta Error (Type II) Power calculation Increasing power and decreasing beta error V. Assignments & Grading Assignment sheets will be distributed periodically throughout the school year. Homework will be assigned on a daily basis. Grades will be based on quizzes and tests; in addition, teachers may use homework, group activities and/or projects for grading purposes. All students will take departmental midyear and final examinations. The Radnor High School grading system and scale will be used to determine letter grades. Revised: March 10, 2016 Revised: March 10, 2016