AP Statistics

Course Description

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AP Statistics Course Description:
Prerequisites: Integrated Math 3 or Algebra 2 (required), Integrated Math 3 Honors, Introduction
to Calculus, or Math Analysis/Trig (recommended)
Course Overview: AP Statistics gives students hands-on experience collecting, analyzing,
graphing, and interpreting real-world data. They will learn to effectively design and analyze
research studies by reviewing and evaluating real research examples taken from daily life.
Students are regularly shown the connections between prior learning and new topics and are
required to identify those connections when faced with new situations. For example, when using
sample data to make inferences about a population, students draw on prior knowledge of
sampling techniques, data distributions, and probability to make those necessary inferences.
Students are required to use appropriate research techniques to design, carry out, and analyze
the results of controlled experiments. The next time they hear the results from a poll or study,
they can use these skills to determine whether the results are valid. As the art of drawing
conclusions from imperfect data and the science of real world uncertainties, statistics plays an
important role in many fields. Students completing this course are trained and well-prepared to
use the skills they acquire in this course to apply their knowledge to those fields. The equivalent
of an introductory college-level course, AP Statistics prepares students for the AP Exam and for
further study in science, sociology, medicine, engineering, political science, geography, and

Course Content:

• The Role of Statistics and the Data Analysis Process
• Collecting Data Sensibly
• Graphical Methods for Describing Data
• Numerical Methods for Describing Data
• Summarizing Bivariate Data
• Probability
• Random Variables and Probability Distributions
• Sampling Variability and Sampling Distributions
• Estimation Using a Single Sample
• Hypothesis Testing Using a Single Sample
• Comparing Two Populations or Treatments
• The Analysis of Categorical Data and Goodness-of-Fit Tests
• Simple Linear Regression and Correlation: Inferential Methods
• Multiple Regression Analysis
• Analysis of Variance

Textbook: Introduction to Statistics and Data Analysis, Peck, R., Olsen, C., Devore, J., 4th edition,
Brooks/Cole Publishing.