AP Statistics Syllabus

This course will introduce students to the major concepts and tools for collecting, analyzing, and drawing conclusions from data. They are exposed to four broad conceptual themes:

1. Exploring data

2. Planning a study

3. Anticipating patterns in advance

4. Statistical inference

The primary text provides the general layout of the course. Teaching materials for the course come from textbooks, newspapers, videos, and the World Wide Web. All students have access to TI-83/TI-84 calculators at school and at home. For most one computer simulation assignment is made. Minitab Statistical Software is used. Students are also instructed in the use of Excel for data analysis. Students are expected to read the material in the text prior to class to facilitate discussion.

Emphasis is placed on teaching the students to communicate effectively using correct statistical vocabulary. All tests include one or more free response questions from previous AP exams. Responses must be in complete sentences. Using previous AP questions teaches the students to make the connections between the different aspects of the statistical process.

Projects are a major part of the course. Projects allow the students to apply concepts to a topic of personal interest (with teacher approval). They are encouraged to choose meaningful topics. Students work in pairs, collaborate on data collection and write-up of project results. The first semester project is using descriptive statistics. Students usually have two months to complete the project and submit the written report complete with meaningful graphical displays. The second project is a semester-long project using inferential statistics. Students must demonstrate a thorough understanding of the statistical process, including design, analysis, and appropriate conclusions based on the data. Students may use available data from reliable sources or may choose to generate their own data using correct collection procedures. After submitting the completed paper, students are expected to present their project and results to their classmates and invited guests.

Statistics Project Guidelines

2nd Semester

1. The project must be typed and double-spaced.

2. All charts, data sheets, and graphs should be neatly constructed and written in ink (only if not done on computer). They do not have to be typed. Graphs and charts should have a title and properly labeled axes.

3. All mathematical formulas must be given when computing test statistics. The substitution step (when possible) should be shown before numerical answers are given. When using variables, be sure to state what each represents.

4. All pages should be numbered.

5. Order of pages:

A. COVER SHEET – The first page of the project must be a cover sheet that includes your name, date,

teacher’s name and the title of the project.

B. TABLE OF CONTENTS

C. INTRODUCTION

1. Statement of the problem: Indicates the variables of interest and the specific relationship

between those variables to be investigated. The statement should identify all variables. It should

present the background of the problem as well as the justification for the project in terms of the

significance of the problem.

2. Review of related literature: Read and summarize sources containing information related to the

research problem. The review will provide the rationale for your research hypothesis.

3. Statement of the hypothesis: Null hypothesis only.

D. EXPLANATION OF DATA – This should include how the data were collected (randomness, etc) or

the research done to collect the data. Remember to document all items that need to be cited.

E. ANALYSIS OF DATA – This is where you include all statistical tests. Your charts and graphs go here.

F. PROBLEMS IN THE PROJECT – Limitations of your inferences should be discussed.

G. CONCLUSION – This is where you interpret your findings (what can you conclude or not conclude

from your research).

H. DISCUSSION – Suggestions for further work in the area of your topic as well as recommendations are

mentioned here.

I. WORKS CITED

J. APPENDIX – this is where you include your data, sample surveys, cover letters, and any other handouts

or information you used in your project.

6. Final Presentation – The completed project will be due two weeks before final exams. An exact date will

be announced.

7. An oral presentation will be required.

Evaluation

1. Creativity and originality.

2. Organization and neatness. (Does the report adhere to format guidelines?)

3. Clarity (vocabulary, English structure, data, charts).

4. **Date of completion – All work must be submitted on or before the due date.

5. Validity of conclusions. (Was the objective accomplished?)

Primary Textbook References and Resource Materials

(Noted with the following letters in the Course Outline)

T Yates, Daniel S., Moore, David S. and Starnes, Darren S. The Practice of Statistics. 2nd ed. New York:

W. H. Freeman, 2003.

GRB Yates, Daniel S,. and Starnes, Darren S. Golden Resource Binder. New York: W.H. Freeman, 2002.

V Annenberg/CPB. Against All Odds: Inside Statistics. 26 30-min. Washington, DC,: The Annenberg/CPB

Collection, 1989. Videos. Http://www.learner.org.

WK Rossman, Allan J. Workshop Statistics: Discovery With Data. New York: Springer-Verlag, 1996.

POD Peck, Olsen, and Devore. Introduction to Statistics and Data Analysis. 2nd ed. Brooks/Cole, 2005.

R Bohan, James F. AP Statistics: Preparing for the Advanced Placement Examination. New York: AMSCO

School Publications, 2000.

W Chapter review worksheets.

HW Suggested problems for homework assignments from Yates, Moore, and Starnes textbook.

Technology

TI-83/TI-84 Calculators

Minitab Statistical Software

Microsoft Office Excel

Course Outline

Approx # of days	Topics and Activities	Assignments
1	Introduction to Statistics V: What is Statistics?
7	Exploring Data Graphical displays of distributions of univariate data: boxplots, stemplots, dotplots, histograms, frequency charts, cumulative frequency charts. Summarize distributions of univariate data by determining and interpreting measures of center, spread, positions, and effects of changing measurements and linear transformation on summary measures. V: Describing Distributions GRB: Computer exercise - Did Mr. Starnes stack his class? Activity: M&Ms describing distributions Test	HW Chapter 1: 5-10, 16, 18, 23-28, 31-35, 40,41, 44-46, 52, 53-57 W: Chapter 1
7	Normal Distributions Investigate the properties of the normal distribution. Standardized scores, use the normal distribution as a model for measurement. Analyze distribution of continuous data both normal and non-normal. Compare distributions among sets of univariate data. Construct normality plots. V: Normal Distributions GRB: computer exercise - Exploring normal distributions. Test	HW Chapter 2: 2-4, 6-9, 11-16, 21-25, 28-36, 38-48 W: Chapter 2
10	Examining Relationships Analyze bivariate data. Interpret scatterplots. Determine explanatory and response variables. Recognize and analyze correlation and linearity, coefficient of determination. Determine the least squares regression line. Create residual plots and identify outliers and influential points V: Describing Relationships GRB: Computer exercise - Can we predict SAT-V from SAT- M? Calculator: Anscombe data sets Activity: M&Ms Least squares regression Activity Worksheets: 1 Sibling Scatter Plots. 2 Leonardo's Essay on Body Proportions Test	HW 1-4, 16-19, 23, 29, 30, 33-37, 50-52, 55, 58-60 W: Chapter 3

11	More on Two-Variable Data Model nonlinear data and use transformations to achieve linearity. Prediction in the exponential growth model. Determine the best model for bivariate data, cautions about correlation and regression, relations in categorical data, Simpson's Paradox. V: The Question of Causation Activity: M&Ms Non-Linear Regression - The Decay Function Problem Test	HW 17, 19, 20, 24, 25, 38-45, 49 W: Chapter 4
10	Producing Data Observation vs experiment Experimental design and sampling. Different methods of data collection, simple random sampling, sampling error, bias, stratifying, confounding, blocking, replication. Design experiments and simulations of experiments. V: Experimental Design V: Blocking and Sampling V: Samples and Surveys R: Planning a study T: Simulations with the computer p.315 Activity Worksheet: Experimental Design Test	HW 1-10, 19-27, 50-53, 56,58, 68-72 W: Chapter 5 * A project using descriptive statistics is assigned at this time.
10	Probability: The Study of Randomness Find the probability of a random phenomenon. Use probability models, rules of probability, and conditional probabilities. Simulations as a means to answer probability questions. V: What is probability? Activity: M&Ms Probability exercises Use Excel spreadsheet to compute probabilities Test	HW 2, 4, 8-10, 19-23, 34-40, 43,44, 67-70, 73, 74, 77 W: Chapter 6
8	Random Variables Discrete and continuous random variables, mean and standard deviation of discrete random variables, Law of Large Numbers, rules for means and variances. V: Random Variables GRB: Test 7C T: Ex. 7.63 Slim Again computer simulation Test	HW 4-8, 10-17, 36-39, 45-50 W: Chapter 7

8	Binomial and Geometric Distributions Binomial probabilities, binomial distributions, binomial formulas, mean, standard deviation, expected value, normal approximation to the binomial distribution, geometric distributions and probabilities associated with geometric distributions. V: Binomial Distributions Activity: M&M Toss Activity: M&Ms ITunes Test	HW 3-8, 9-14, 15-17, 28-35, 37-39, 47, 49, 50, 53 W: Chapter 8
9	Sampling Distributions Parameter vs statistic, heading toward inference, sampling distributions, sampling variability and bias, sampling distribution of sample proportions, sampling distribution of sample means, the Central Limit Theorem. WK: TI calculator - Cents and the Central Limit Theorem Activity: Simulation of Central Limit Theorem using Excel Test	HW 1-4, 5, 6, 8-13, 15, 16, 20-24, 28, 30-34, 38 W: Chapter 9
9	Review and Semester Exam
13	Introduction to Inference Estimating with confidence, confidence interval for a population mean, how confidence intervals behave, choosing sample size, logic of significance tests, stating hypotheses, P-values and statistical significance, carrying out significance tests, test from a confidence interval, statistical significance, practical significance, concepts of Type I and Type II errors and power. V: Confidence Intervals V: Significance Tests Activity: Type I & Type II errors - O.J. Simpson trial (WWW) Test	HW 1-4, 6-9, 12-23, 25, 27-34, 38, 39, 42-48, 51-55, 57-62, 66, 69 W: Chapter 10 ** 2nd Semester Project using inferential statistics is assigned at this time.

10	Inference for Distributions The t-distributions, intervals and significance tests with t, matched pairs, robustness of t-procedures, comparing two population means. V: Inference for One Mean V: Comparing Two Means Activity: M&Ms Inference Problems Activity: M&Ms 2-Sample T-Test Activity: Jumping Frogs Activity: M&Ms Bull's Eye (matched pairs) Test	HW 1-4, 7-21, 39-41, 43, 47-52, 56, 58, 62, 64, 67 W: Chapter 11
8	Inference for Proportions Inference for a population proportion, Z procedures and sample size, margin of error, comparing two proportions, significance tests for difference in two proportions, pooled estimate of p. V: Inference for Proportions Activity: How much of the earth is covered by water? Activity: M&Ms Statistical difference between two proportions Test	HW 1-7, 10-14, 22, 23, 26, 27 W: Chapter 12
10	Inference for Tables: Chi-Square Procedures Tests for goodness of fit, properties of Chi-square distributions, conducting inference by simulation, inference for two-way tables, chi-square test for homogeneity of populations, Chi-square test of independence. V: Inference for Two-Way Tables Activity: M&Ms Chi-square goodness of fit Activity: M&Ms Chi-square test of association Test	HW 1-4, 9, 14-24 W: Chapter 13
7	Inference for Regression Inference about the model, confidence intervals for regression slope, predictions and conditions. V: Inference for Relationships Test	HW 1-4, 6, 10, 11, 14, 15 W: Chapter 14

14	Review for AP Exam Students complete two released AP exams. Scoring of the exam is discussed. Other practice exams are taken.
4	Presentations of Projects
16	Post AP Exam Topics Inference for population spread, the F-test, one-way analysis of variance, analysis of variance F-test, the idea of analysis of variance, conditions for ANOVA