STATS : Data and Models

by De Veaux, Richard D.; Velleman, Paul F.; Bock, David E.

• ISBN13: 9780321200549
• ISBN10: 0321200543
• Edition: 2nd
• Format: Hardcover w/CD
• Copyright: 2008-01-01
• Publisher: Addison Wesley

Summary

This book is written for the introductory statistics course and students majoring in any field. It is written in an approachable, informal style that invites students to think about how to reason when data is available. Stats: Data and Models (SDM), as compared to Intro Stats, offers Math Boxes, which present the mathematical underpinnings of the statistical methods and concepts, and advanced topics (Ch. 28-31) that are often covered in a two-semester course, plus the inclusion of non-parametrics. SDM carries a core focus on statistical thinking and understanding analyses throughout the text, emphasizing how statistics helps us to understand the world. the book also recognizes the central role that technology plays in statistics. SDM is organized into short teachable chapters that focus on one topic at a time, offering instructors flexibility in selecting topics while students receive digestible chunks of information that build on previous material before moving on.

Table of Contents

Exploring and Understanding Data

Stats Starts Here

Data

Displaying Categorical Data

Displaying Quantitative Data

Describing Distributions Numerically

The Standard Deviation as a Ruler and the Normal Model

Exploring Relationships between Variables

Scatterplots, Association, and Correlation

Linear Regression

Regression Wisdom

Re-Expressing Data: It's easier than you think

Gathering Data

Understanding Randomness

Sample Surveys

Experiments

Randomness and Probability

From Randomness to Probability

Probability Rules!

Random Variables

Probability Models

From The Data at Hand to the World at Large

Sampling Distribution Models

Confidence Intervals for Proportions

Testing Hypotheses about Proportions

More About Tests

Comparing Two Proportions

Learning About the World

Inferences About Means

Comparing Means

Paired Samples and Blocks

Modeling the World

Inferences for Regression

Analysis of Variance

Two Way Analysis of Variance

Multiple Regression

Multiple Regression Wisdom

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