Worldwide Statistics: Think & Do for use with AP® Statistics


Scott Stevens– Champlain College

ISBN-10: 0-9885572-3-1
ISBN-13: 978-0-9885572-3-9
318 pages
©2019 Worldwide Center of Mathematics, LLC

Digital | $9.95
Print | $29.95

www.StevensStats.com

Introduction

Stevens’ AP Statistics: Think & Do, is a new kind of textbook/workbook that integrates theoretical content with demonstrative examples and exercises in a page by page bullet-point format, with content fully adapted to the AP curriculum. The streamlined presentation of information makes this book ideal for any busy AP student. It is organized in such a way that new content is initially summarized at the top of the page, followed by a completed demonstrative example and then immediately followed by a “Your Turn” unfinished example for the students to complete. While this format is certainly typical in a classroom lecture, it is often difficult for the students to keep up with the lecture or faithfully map the lecture material to the corresponding content found in a traditional textbook. Stevens’ book alleviates these problems by combining lecture notes, examples, exercises, and textbook content into a single, well-organized workbook. This book is meticulously constructed in such a way that each page can be presented as an overhead slide. Unlike many textbooks, the presentation is not written in a conversational tone. Rather, it is presented in bullet-point format, greatly increasing its effectiveness as a study tool for the AP test. This also allows the instructor to discuss the material in a context of their preference without being confined to the way a traditional textbook might present information. This is an affordable one-time-use book with space provided for students to apply the printed material and complete examples in class. Recognizing that every AP Statistics class has a lot of material to cover in a restricted amount of time, this text/workbook is designed for instructors who feel they currently spend too much time presenting new material and not enough time ‘doing’ it.


Contents

  • 1.1 Statistics and Data
  • 1.2 Sampling
  • 1.3 Lying with Statistics and Percentages
  • 1.4 Observational Studies and Experiments
  • 2.1 Averages
  • 2.2 Range, Standard Deviation, and Variance
  • 2.3 Measures of Relative Standing: z-scores
  • 2.4 Measures of Relative Standing: Quartiles, Percentiles, and Box Plots
  • 2.5 Weighted Averages and Simpson’s Paradox
  • 3.1 Frequency Distributions
  • 3.2 Histograms
  • 3.3 Other Graphs for Quantitative Data
  • 3.4 Tables and Graphs for Qualitative Data
  • 4.1 Basics
  • 4.2 Conditional Probability
  • 4.3 The Addition Rule
  • 4.4 The Multiplication Rule
  • 4.5 One Bad Apple – Probabilities of At Least One
  • 5.1 Discrete Random Variables and Probability Distibutions
  • 5.2 Binomial Probability Distributions
  • 5.3 Mean and Standard Deviation of a Binomial Distribution
  • 5.4 The Geometric Distribution
  • 6.1 Continuous Random Variables and the Standard Normal Distribution
  • 6.2 Normal Distributions in General
  • 6.3 Sampling Distributions
  • 6.4 The Central Limit Theorem
  • 6.5 The Normal Approximation to the Binomial Distribution
  • 7.1 Introduction to Confidence Intervals
  • 7.2 Estimating a Population Mean and Sample Size (σ known)
  • 7.3 Estimating a Population Proportion and Sample Size
  • 7.4 Estimating a Population Mean (σ unknown)
  • 7.5 A Summary and Some Loose Ends
  • 8.1 Foundations of Hypothesis Testing
  • 8.2 Hypothesis Tests About a Proportion
  • 8.3 Hypothesis Tests About a Mean: σ Not Known
  • 8.4 Hypothesis Tests About a Mean: σ Known (optional)
  • 9.1 Hypothesis Tests for Mean Differences: Paired Data
  • 9.2 Hypothesis Tests for Two Means: Independent Data
  • 9.3 Hypothesis Tests for Two Proportions
  • 10.1 Correlation
  • 10.2 Linear Regression
  • 10.3 Linearity and Transformations
  • 10.4 The Hypothesis Test Behind the Scenes
  • 10.5 Multiple Linear Regression: Controlling for Variables – An Introduction
  • 11.1 Chi-Squared Test for Goodness of Fit
  • 11.2 Chi-Squared Test of Independence
  • 11.3 ANOVA – An Introduction