In addition to providing cases and real data to demonstrate real business situations, this text provides resources to support understanding and engagement.
1. A successful problem-solving framework in the "4-M Examples" (Motivation, Method, Mechanics, Message) model a clear outline for solving problems.
2. "New What Do You Think" questions give students an opportunity to stop and check their understanding as they read.
3. New learning objectives guide students through each chapter and help them to review major goals.
4. "Software Hints" provide instructions for using the most up-to-date technology packages.
5. The second edition also includes expanded coverage and instruction of Excel® 2010 and the XLSTAT™ add-in.
Ch 1 Introduction
Ch 2 Data
Ch 3 Describing Categorical Data
Ch 4 Describing Numerical Data
Ch 5 Association between Categorical Variables
Ch 6 Association between Quantitative Variables
Ch 7 Probability
Ch 8 Conditional Probability
Ch 9 Random Variables
Ch10 Association between Random Variables
Ch11 Probability Models for Counts
Ch12 The Normal Probability Model
Ch13 Samples and Surveys
Ch14 Sampling Variation and Quality
Ch15 Confidence Intervals
Ch16 Statistical Tests
Ch18 Inference for Counts
Ch19 Linear Patterns
Ch20 Curved Patterns
Ch21 The Simple Regression Model
Ch22 Regression Diagnostics
Ch23 Multiple Regression
Ch24 Building Regression Models
Ch25 Categorical Explanatory Variables
Ch26 Analysis of Variance
Ch27 Time Series
Ch28 Alternative Approaches to Inference
Ch29 Regression with Big Data
Ch30 Two-Way Analysis of Variance