Introductory Statistics, MyLab Revision, 10th edition

  • Neil A. Weiss

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Overview

Introductory Statistics includes careful, detailed explanations to ease the learning process. With more than 1,000 data sets and more than 3,000 exercises, this text takes a data-driven approach that encourages you to apply your knowledge and develop statistical understanding.

Published by Pearson (July 15th 2020) - Copyright © 2020

ISBN-13: 9780136872832

Subject: Introductory Statistics

Category: Introductory Statistics, MyLab Revision

Table of contents

Table of Contents

  • Indicates optional material.
  • ∗∗Indicates optional material on the WeissStats site.

PART I: Introduction

  1. The Nature of Statistics
    • Case Study: Top Films of All Time
    • 1.1 Statistics Basics
    • 1.2 Simple Random Sampling
    • 1.3 Other Sampling Designs∗
    • 1.4 Experimental Designs∗
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography

PART II: Descriptive Statistics

  1. Organizing Data
    • Case Study: World’s Richest People
    • 2.1 Variables and Data
    • 2.2 Organizing Qualitative Data
    • 2.3 Organizing Quantitative Data
    • 2.4 Distribution Shapes
    • 2.5 Misleading Graphs∗
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  2. Descriptive Measures
    • Case Study: The Beatles’ Song Length
    • 3.1 Measures of Center
    • 3.2 Measures of Variation
    • 3.3 Chebyshev’s Rule and the Empirical Rule∗
    • 3.4 The Five-Number Summary; Boxplots
    • 3.5 Descriptive Measures for Populations; Use of Samples
    • Chapter in Review
    • Review Problems
    • Focusing on Data
    • Analysis
    • Case Study Discussion
    • Biography

PART III: Probability, Random Variables, and Sampling Distributions

  1. Probability Concepts
    • Case Study: Texas Hold’em
    • 4.1 Probability Basics
    • 4.2 Events
    • 4.3 Some Rules of Probability
    • 4.4 Contingency Tables; Joint and Marginal Probabilities∗
    • 4.5 Conditional Probability∗
    • 4.6 The Multiplication Rule; Independence∗
    • 4.7 Bayes’s Rule∗
    • 4.8 Counting Rules∗
    • Chapter in Review 218
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  2. Discrete Random Variables
    • Case Study: Aces Wild on the Sixth at Oak Hill
    • 5.1 Discrete Random Variables and Probability Distributions∗
    • 5.2 The Mean and Standard Deviation of a Discrete Random Variable∗
    • 5.3 The Binomial Distribution∗
    • 5.4 The Poisson Distribution∗
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  3. The Normal Distribution
    • Case Study: Chest Sizes of Scottish Militiamen
    • 6.1 Introducing Normally Distributed Variables
    • 6.2 Areas under the Standard Normal Curve
    • 6.3 Working with Normally Distributed Variables
    • 6.4 Assessing Normality; Normal Probability Plots
    • 6.5 Normal Approximation to the Binomial Distribution∗
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  4. The Sampling Distribution of the Sample Mean
    • Case Study: The Chesapeake and Ohio Freight Study
    • 7.1 Sampling Error; the Need for Sampling Distributions
    • 7.2 The Mean and Standard Deviation of the Sample Mean
    • 7.3 The Sampling Distribution of the Sample Mean
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography

PART IV: Inferential Statistics

  1. Confidence Intervals for One Population Mean
    • Case Study: Bank Robberies: A Statistical Analysis
    • 8.1 Estimating a Population Mean
    • 8.2 Confidence Intervals for One Population Mean When σ Is Known
    • 8.3 Confidence Intervals for One Population Mean When σ Is Unknown
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  2. Hypothesis Tests for One Population Mean
    • Case Study: Gender and Sense of Direction
    • 9.1 The Nature of Hypothesis Testing
    • 9.2 Critical-Value Approach to Hypothesis Testing
    • 9.3 P-Value Approach to Hypothesis Testing
    • 9.4 Hypothesis Tests for One Population Mean When σ Is Known
    • 9.5 Hypothesis Tests for One Population Mean When σ Is Unknown
    • 9.6 The Wilcoxon Signed-Rank Test∗
    • 9.7 Type II Error Probabilities; Power∗
    • 9.8 Which Procedure Should Be Used?∗∗
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  3. Inferences for Two Population Means
    • Case Study: Dexamethasone Therapy and IQ
    • 10.1 The Sampling Distribution of the Difference between Two Sample Means for Independent Samples
    • 10.2 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Assumed Equal
    • 10.3 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Not Assumed Equal
    • 10.4 The Mann—Whitney Test∗
    • 10.5 Inferences for Two Population Means, Using Paired Samples
    • 10.6 The Paired Wilcoxon Signed-Rank Test∗
    • 10.7 Which Procedure Should Be Used?∗∗
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  4. Inferences for Population Standard Deviations
    • Case Study: Speaker Woofer Driver Manufacturing
    • 11.1 Inferences for One Population Standard Deviation∗
    • 11.2 Inferences for Two Population Standard Deviations, Using Independent Samples∗
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  5. Inferences for Population Proportions
    • Case Study: Arrested Youths
    • 12.1 Confidence Intervals for One Population Proportion
    • 12.2 Hypothesis Tests for One Population Proportion
    • 12.3 Inferences for Two Population Proportions
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  6. Chi-Square Procedures
    • Case Study: Eye and Hair Color
    • 13.1 The Chi-Square Distribution
    • 13.2 Chi-Square Goodness-of-Fit Test
    • 13.3 Contingency Tables; Association
    • 13.4 Chi-Square Independence Test
    • 13.5 Chi-Square Homogeneity Test
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography

PART V: Regression, Correlation, and ANOVA

  1. Descriptive Methods in Regression and Correlation
    • Case Study: Healthcare: Spending and Outcomes
    • 14.1 Linear Equations with One Independent Variable
    • 14.2 The Regression Equation
    • 14.3 The Coefficient of Determination
    • 14.4 Linear Correlation
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  2. Inferential Methods in Regression and Correlation
    • Case Study: Shoe Size and Height
    • 15.1 The Regression Model; Analysis of Residuals
    • 15.2 Inferences for the Slope of the Population Regression Line
    • 15.3 Estimation and Prediction
    • 15.4 Inferences in Correlation
    • 15.5 Testing for Normality∗∗
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  3. Analysis of Variance (ANOVA)
    • Case Study: Self-Perception and Physical Activity
    • 16.1 The F-Distribution
    • 16.2 One-Way ANOVA: The Logic
    • 16.3 One-Way ANOVA: The Procedure
    • 16.4 Multiple Comparisons∗
    • 16.5 The Kruskal—Wallis Test∗
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography

PART VI: Multiple Regression and Model Building; Experimental Design and ANOVA∗∗

  • MODULE A: Multiple Regression Analysis
    • Case Study: Automobile Insurance Rates
    • A.1 The Multiple Linear Regression Model
    • A.2 Estimation of the Regression Parameters
    • A.3 Inferences Concerning the Utility of the Regression Model
    • A.4 Inferences Concerning the Utility of Particular Predictor Variables
    • A.5 Confidence Intervals for Mean Response; Prediction Intervals for Response
    • A.6 Checking Model Assumptions and Residual Analysis
    • Module in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Answers to Selected Exercises
    • Index
  • MODULE B: Model Building in Regression
    • Case Study: Automobile Insurance Rates–Revisited
    • B.1 Transformations to Remedy Model Violations
    • B.2 Polynomial Regression Model
    • B.3 Qualitative Predictor
    • B.4 Multicollinearity
    • B.5 Model Selection: Stepwise Regression
    • B.6 Model Selection: All-Subsets Regression
    • B.7 Pitfalls and Warnings
    • Module in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Answers to Selected Exercises
    • Index
  • MODULE C: Design of Experiments and Analysis of Variance
    • Case Study: Dental Hygiene: Which Toothbrush?
    • C.1 Factorial Designs
    • C.2 Two-Way ANOVA: The Logic
    • C.3 Two-Way ANOVA: The Procedure
    • C.4 Two-Way ANOVA: Multiple Comparisons
    • C.5 Randomized Block Designs
    • C.6 Randomized Block ANOVA: The Logic
    • C.7 Randomized Block ANOVA: The Procedure
    • C.8 Randomized Block ANOVA: Multiple Comparisons
    • C.9 Friedman’s Nonparametric Test for the Randomized Block Design
    • Module in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion

Answers to Selected Exercises

Index

Appendix A: Statistical Tables

Appendix B: Answers to Selected Exercises

Index

Photo Credits

Indicates optional material.

∗∗Indicates optional material on the WeissStats site.

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