Rowman & Littlefield Publishers

Pages: 696
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978-1-5381-0982-3 • Hardback • January 2019 • $180.00 • (£120.00)

978-1-5381-0983-0 • Paperback • January 2019 • $99.00 • (£65.00)

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Nancy Whittier is Sophia Smith Professor of Sociology at Smith College. She has taught statistics and research methods for 25 years, and also teaches classes on gender, sexuality, and social movements. She is the author of Frenemies: Feminists, Conservatives, and Sexual Violence (Oxford University Press, 2018), The Politics of Child Sexual Abuse: Emotions, Social Movements, and the State (Oxford University Press, 2009) and numerous articles on social movements, gender, and sexual violence.

Tina Wildhagen is Associate Professor of Sociology and Dean of the Sophomore Class at Smith College. She has taught statistics and quantitative research methods for more than a decade, and also teaches courses on privilege and power in American education, inequality in higher education.

Howard J. Gold is Professor of Government at Smith College. He has taught statistics for 30 years, and also teaches courses on American elections, public opinion and the media, and political behavior. His research focuses on public opinion, partisanship, and voting behavior.

Preface

About the Authors

Chapter 1 Introduction

Why Study Statistics?

Research Questions and the Research Process

Pinning Things Down: Variables and Measurement

Units of Analysis

Measurement Error: Validity and Reliability

Levels of Measurement

Causation: Independent and Dependent Variables

Getting the Data: Sampling and Generalizing

Sampling Methods

Sources of Secondary Data: Existing Data Sets, Reports, and “Big Data”

Big Data

Growth Mindset and Math Anxiety

Using This Book

Statistical Software

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 2 Getting to Know Your Data

Frequency Distributions

Percentages and Proportions

Cumulative Percentage and Percentile

Percent Change

Rates and Ratios

Rates

Ratios

Working with Frequency Distribution Tables

Missing Values

Simplifying Tables by Collapsing Categories

Graphical Displays of a Single Variable: Bar Graphs, Pie Charts, Histograms, Stem-and-Leaf Plots, and Frequency Polygons

Bar Graphs and Pie Charts

Histograms

Stem-and-Leaf-Plots

Frequency Polygons

Time Series Charts

Comparing Two Groups On the Same Variable Using Tables, Graphs, and Charts

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 3 Examining Relationships between Two Variables

Cross-Tabulations and Relationships between Variables

Independent and Dependent Variables

Column, Row, and Total Percentages

Interpreting the Strength of Relationships

Interpreting the Direction of Relationships

Graphical Representations of Bivariate Relationships

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 4 Typical Values in a Group

What Does It Mean to Describe What Is Typical?

Mean

Median

Mode

Finding the Mode, Median, and Mean in Frequency Distributions

Choosing the Appropriate Measure of Central Tendency

Median Versus Mean Income

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 5 The Diversity of Values in a Group

Range

Interquartile Range

Standard Deviation

Using the Standard Deviation to Compare Distributions

Comparing Apples and Oranges

Skewed Versus Symmetric Distributions

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 6 Probability and the Normal Distribution

The Rules of Probability

The Addition Rule

The Complement Rule

The Multiplication Rule with Independence

The Multiplication Rule without Independence

Applying the Multiplication Rule with Independence to the “Linda” and “Birth-Order” Probability Problems

The Normal Distribution

Standardizing Variables and Calculating Z-Scores

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 7 From Sample to Population

Repeated Sampling, Sample Statistics, and the Population Parameter

Sampling Distributions

Finding the Probability of Obtaining A Specific Sample Statistic

Estimating the Standard Error from a Known Population Standard Deviation

Finding and Interpreting the Z-Score for Sample Means

Finding and Interpreting the Z-Score for Sample Proportions

The Impact of Sample Size On the Standard Error

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 8 Estimating Population Parameters

Inferential Statistics and the Estimation of Population Parameters

Confidence Intervals Manage Uncertainty Through Margins of Error

Certainty and Precision of Confidence Intervals

Confidence Intervals for Proportions

Constructing a Confidence Interval for Proportions: Examples

Confidence Intervals for Means

The t-Distribution

Calculating Confidence Intervals for Means: Examples

The Relationship Between Sample Size and Confidence Interval Range

The Relationship Between Confidence Level and Confidence Interval Range

Interpreting Confidence Intervals

How Big a Sample?

Assumptions for Confidence Intervals

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 9 Differences between Samples and Populations

The Logic of Hypothesis Testing

Null Hypotheses (H0) and Alternative Hypotheses (Ha)

One-Tailed and Two-Tailed Tests

Hypothesis Tests for Proportions

The Steps of the Hypothesis Test

One-Tailed and Two-Tailed Tests

Hypothesis Tests for Means

Example: Testing a Claim about a Population Mean

Error and Limitations: How Do We Know We are Correct?

Type I and Type II Errors

What Does Statistical Significance Really Tell Us? Statistical and Practical Significance

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 10 Comparing Groups

Two-Sample Hypothesis Tests

The Logic of the Null Hypothesis and Alternative Hypothesis in Two-Sample Tests

Notation for Two-Sample Tests

The Sampling Distribution for Two-Sample Tests

Hypothesis Tests for Differences Between Means

Confidence Intervals for Differences Between Means

Hypothesis Tests for Differences Between Proportions

Confidence Intervals for Differences Between Proportions

Statistical and Practical Significance in Two-Sample Tests

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 11 Testing Mean Differences among Multiple Groups

Comparing Variation Within and Between Groups

Hypothesis Testing Using Anova

Analysis of Variance Assumptions

Determining Which Means are Different: Post-Hoc Tests

Anova Compared to RepeateD t-Tests

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 12 Testing the Statistical Significance of Relationships in Cross-Tabulations

The Logic of Hypothesis Testing with Chi-Square

The Steps of a Chi-Square Test

Size and Direction of Effects: Analysis of Residuals

Example: Gender and Perceptions of Health

Assumptions of Chi-Square

Statistical Significance and Sample Size

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 13 Ruling Out Competing Explanations for Relationships between Variables

Criteria for Causal Relationships

Modeling Spurious Relationships

Modeling Non-Spurious Relationships

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Chapter 14 Describing Linear Relationships between Variables

Correlation Coefficients

Calculating Correlation Coefficients

Scatterplots: Visualizing Correlations

Regression: Fitting a Line to a Scatterplot

The “Best-Fitting” Line

Slope and Intercept

Calculating the Slope and Intercept

Goodness-of-Fit Measures

R-Squared (r^{2})

Standard Error of Prediction

Dichotomous (“Dummy”) Independent Variables

Multiple Regression

Statistical Inference for Regression

The F-Statistic

Standard Error of the Slope

Assumptions of Regression

Chapter Summary

Using Stata

Using SPSS

Practice Problems

Solutions to Odd Numbered Practice Problems

Glossary

Appendix A Normal Table

Appendix B Table of t-Values

Appendix C F-Table, for Alpha = .05

Appendix D Chi-Square Table

Appendix E Selected List of Formulas

Appendix F Choosing Tests for Bivariate Relationships

Index

View samples chapters of the Front Matter, Chapter 1, Chapter 3, and Chapter 9.- Stata and SPSS explanations and examples in every chapter.

- Statistics analysis taught in the way it is used in the social sciences.

- Real world applications integrated throughout the chapters.

- Research on the teaching and learning of quantitative material incorporated into the content.

- Multiple types of practice problems provided both in the text and on the open access Companion Website.

- Instructor and student ancillaries written by the authors.

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**Instructor's Manual.** For each chapter, this valuable resource provides a variety of tools such as lecture outlines, student learning objectives, discussion questions, and other resources to simplify classroom preparation.

**Test Bank.** The Test Bank includes a variety of test questions and is available in either Word, PDF or Respondus formats. For every chapter in the text, the Test Bank includes a complete test with a variety of question types, including multiple choice, true false, and essay formats.

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**Lecture Notes.** The Lecture Notes provide the tables and figures from the text.