First Semester Syllabus for AP Statistics

The primary text used for the course is: "T"

Moore, David and George McCabe, Introduction to the Practice of Statistics, 2nd ed., New York: W.H. Freeman, 1993.

References and Resource Materials

"V" The Annenberg/CPB "Against All Odds: Inside Statistics" ( 26 hour-long videos) Burlington, Vermont: The Annenberg/CPB Collection, 1989. (1-800-Learner)

"B" Barbella, Peter, James Kepner and Richard L. Scheaffer, Exploring Measurements, Palo Alto: Dale Seymour Publications, 1994.

"S" Gnanadesikan, Mrudulla, Richard L. Scheaffer and Jim Swift, The Art and Techniques of Simulation, Palo Alto: Dale Seymour Publications, 1987.

"L" Landwehr, James M., Jim Swift, and Ann E. Watkins, Exploring Surveys and Information From Samples, Palo Alto: Dale Seymour Publications, 1987.

"M" Moore, David, Statistics Concepts and Controversies, New York: W.H. Freeman and Company, 1985.

"C" The North Carolina School of Science and Mathematics, Contemporary Precalculus through Applications, Providence, RI: Janson Publications, Inc., 1991.

"A" Scheaffer, Richard L., Mrudulla Gnanadesikan, Ann Watkins, and Jeffrey A. Witmer. Activity Based Statistics. New York: Springer-Verlag, 1996.

"G" Tanur, J. et al (eds.) Statistics: A Guide to the Unknown, 3rd ed. Belmont CA; Wadsworth, 1989.

"F" CBS video "Fact or Fiction",

"O" Other resource materials that are used in the classroom come from articles in newspapers and journals. Students often bring in data sets they collect or download from the World Wide Web.


Week 1

Introduction To Statistics:

Students read about experimental design and the role of statistics in medicine.



G pages 3-15 Essay "The Biggest Public Health Experiment Ever: The 1954 Field Trial of the Salk Poliomyelitis Vaccine"

F video "Fact or Fiction"

O Journal Articles about Experimental Design: Readings from the Harvard Women's Newsletter.

Nova Video "Can You Still Get Polio?"

Week 2 - 3

Exploring Data.

Graphical displays of distributions of univariate data: boxplots, stemplots, histograms, frequency charts. Stress - Center, spread, clusters, gaps, outliers.

Summarizing distributions of univariate data:

Mean, median, mode, range, interquartile range, quartiles, standard deviation, percentiles, standardized scores (z-scores).

Comparing distributions of univariate data.

Compare center, spread, clusters, gaps, outliers and shapes within groups and between dotplots, stemplots and boxplots.


Approximately 2 days are spent in instruction with the TI-83 calculator and 2 days in the computer lab working with Minitab.

Students use data generated in the class for classroom exercises.

Project 1 on distorted graphs is due at the end of week 3.


T pages 1-46

Week 4 - 6

Standard Deviation and variance:

Properties of standard deviation and the effects of changing measurements and linear transformations on summary measures.

The Normal Distribution and Chebyshev's Theorem: Measuring position, quartiles, percentiles Standardized scores, normal relative frequencies. Using the normal distribution as a model for measurement.

Normal quantile plots to assess normality.

Students spend one day in the computer lab standardizing data, graphing normal quantile plots, and interpreting information from the graphical and numerical displays of data.

Project 2 on data collection and representation is due at the end of week 6.


T pages 46-93


V Video: Normal Distributions, Normal Calculations, and Time Series (4,5,6 ).









Week 7-9

Bivariate Data:

Analyzing patterns in scatterplots, time series, smoothing scatterplots, correlation and linearity, least squares regression line, residual plots, outliers, influential points, and transformations to achieve linearity.

Approximately 2 days are spent in instruction with the TI-83 calculator.

One day Minitab lab on calculating the least squares regression line. Students explore the effect of outliers and influential points.

Project 3:

Two days are spent in the classroom for a data collection and curve fitting lab. Pairs of students work together to generating 3 sets of bivariate data. Students use calculators and computers to write equations of the curves that best fit their data and then answer questions about their data collection techniques, inferences from their data, and experimental design.


T pages 96-183.


C pages 143-165.

V Videos: Models for Growth, Describing Relationships, Correlation (7, 8, 9).


Week 10-12

Relations in categorical Data:

Analyzing 2-way tables, conditional relative frequencies and association.

The question of causation:

Anecdotal evidence, observational studies and experiments.


T pages 183-217

V Video:

The Question of Causation (11).

Week 13-14

Experimental Design,Sampling, and Data Collection:

Simple random sampling, sampling error, bias, stratifying,confounding, blocking, replication.

Two days are spent on class activities to develop an understanding of randomness and sampling.

Project 4:

Writing a questionnaire and conducting a survey is due at the end of the 14th week.


T pages 221-276

M pages 3-109

B pages 52-101

L pages 36-51

V Videos: Experimental Design, Blocking and Sampling (12, 13).

Week 15


Basic Probability Rules.

Simulations as a means to answer probability questions.


T pages 279-305

S pages 1-51

Week 16-17

Random variables and sampling distributions:

Simulation of probability distributions and sampling distributions.

Expected values, standard deviation of a random variable, mean and standard deviation for sums and differences of independent random variables.


One day is spent in the computer lab exploring randomness and simulating probability distributions.


T pages 306-365.

V Video: Samples and Surveys (14).

Week 18

Review and Final Exam.

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