Essential Statistics for the Behavioral Sciences

Second Edition

Gregory J. Privitera - St. Bonaventure University

Courses:
Introduction to Statistics | Quantitative Research Methods in Education | Research Methods | Statistics in Psychology

December 2017 | 640 pages | SAGE Publications, Inc

Essentials of Statistics for the Behavioral Sciences is a concise version of Statistics for the Behavioral Sciences by award-winning teacher, author, and advisor Gregory J. Privitera. The Second Edition provides balanced coverage for today’s students, connecting the relevance of core concepts to daily life with new introductory vignettes for every chapter, while speaking to the reader as a researcher when covering statistical theory, computation, and application. Robust pedagogy allows students to continually check their comprehension and hone their skills while working through carefully developed problems and exercises that include current research and seamless integration of IBM® SPSS® Statistics. Readers will welcome Privitera’s thoughtful instruction, conversational voice, and application of statistics to real-world problems.

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About the Author

Acknowledgments

Preface to the Instructor

To the Student—How to Use SPSS With This Book

PART I: INTRODUCTION AND DESCRIPTIVE STATISTICS

Chapter 1: Introduction to Statistics

1.1 The Use of Statistics in Science

1.2 Descriptive and Inferential Statistics

1.3 Research Methods and Statistics

1.4 Scales of Measurement

1.5 Types of Variables for Which Data Are Measured

1.6 Research in Focus: Evaluating Data and Scales of Measurement

1.7 SPSS in Focus: Entering and Defining Variables

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

Chapter 2: Summarizing Data: Frequency Distributions in Tables and Graphs

2.1 Why Summarize Data?

2.2 Frequency Distributions for Grouped Data

2.3 Identifying Percentile Points and Percentile Ranks

2.4 SPSS in Focus: Frequency Distributions for Quantitative Data

2.5 Frequency Distributions for Ungrouped Data

2.6 Research in Focus: Summarizing Demographic Information

2.7 SPSS in Focus: Frequency Distributions for Categorical Data

2.8 Graphing Distributions: Continuous Data

2.9 Graphing Distributions: Discrete and Categorical Data

2.10 Research in Focus: Frequencies and Percents

2.11 SPSS in Focus: Histograms, Bar Charts, and Pie Charts

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

Chapter 3: Summarizing Data: Central Tendency

3.1 Introduction to Central Tendency

3.2 Measures of Central Tendency

3.3 Characteristics of the Mean

3.4 Choosing an Appropriate

3.5 Research in Focus: Describing Central Tendency

3.6 SPSS in Focus: Mean, Median, and Mode

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

Chapter 4: Summarizing Data: Variability

4.1 Measuring Variability

4.2 The Range and Interquartile Range

4.3 Research in Focus: Reporting the Range

4.4 The Variance

4.5 Explaining Variance for Populations and Samples

4.6 The Computational Formula for Variance

4.7 The Standard Deviation

4.8 What Does the Standard Deviation Tell Us?

4.9 Characteristics of the Standard Deviation

4.10 SPSS in Focus: Range, Variance, and Standard Deviation

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

PART II: PROBABILITY AND THE FOUNDATIONS OF INFERENTIAL STATISTICS

Chapter 5: Probability, Normal Distributions, and z Scores

5.1 Introduction to Probability

5.2 Calculating Probability

5.3 Probability and the Normal Distribution

5.4 Characteristics of the Normal Distribution

5.5 Research in Focus: The Statistical Norm

5.6 The Standard Normal Distribution and z Scores

5.7 A Brief Introduction to the Unit Normal Table

5.8 Locating Proportions

5.9 Locating Scores

5.10 SPSS in Focus: Converting Raw Scores to Standard z Scores

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

Chapter 6: Characteristics of the Sample Mean

6.1 Selecting Samples From Populations

6.2 Selecting a Sample: Who’s In and Who’s Out?

6.3 Sampling Distributions: The Mean

6.4 The Standard Error of the Mean

6.5 Factors That Decrease Standard Error

6.6 SPSS in Focus: Estimating the Standard Error of the Mean

6.7 APA in Focus: Reporting the Standard Error

6.8 Standard Normal Transformations With Sampling Distributions

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

Chapter 7: Hypothesis Testing: Significance, Effect Size, and Power

7.1 Inferential Statistics and Hypothesis Testing

7.2 Four Steps to Hypothesis Testing

7.3 Hypothesis Testing and Sampling Distributions

7.4 Making a Decision: Types of Error

7.5 Testing for Significance: Examples Using the z Test

7.6 Research in Focus: Directional Versus Nondirectional Tests

7.7 Measuring the Size of an Effect: Cohen’s d

7.8 Effect Size, Power, and Sample Size

7.9 Additional Factors That Increase Power

7.10 SPSS in Focus: A Preview for Chapters 8 to 14

7.11 APA in Focus: Reporting the Test Statistic and Effect Size

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

PART III: MAKING INFERENCES ABOUT ONE OR TWO MEANS

Chapter 8: Testing Means: One-Sample t Test With Confidence Intervals

8.1 Going From z to t

8.2 The Degrees of Freedom

8.3 Reading the t Table

8.4 Computing the One-Sample t Test

8.5 Effect Size for the One-Sample t Test

8.6 Confidence Intervals for the One-Sample t Test

8.7 Inferring Significance and Effect Size From a Confidence Interval

8.8 SPSS in Focus: One-Sample t Test and Confidence Intervals

8.9 APA in Focus: Reporting the t Statistic and Confidence Intervals

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

Chapter 9: Testing Means: Two- Independent-Sample t Test With Confidence Intervals

9.1 Introduction to the Between-Subjects Design

9.2 Selecting Samples for Comparing Two Groups

9.3 Variability and Comparing Differences Between Two Groups

9.4 Computing the Two-Independent- Sample t Test

9.5 Effect Size for the Two-Independent- Sample t Test

9.6 Confidence Intervals for the Two-Independent-Sample t Test

9.7 Inferring Significance and Effect Size From a Confidence Interval

9.8 SPSS in Focus: Two-Independent- Sample t Test and Confidence Intervals

9.9 APA in Focus: Reporting the t Statistic and Confidence Intervals

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

Chapter 10: Testing Means: Related-Samples t Test With Confidence Intervals

10.1 Related-Samples Designs

10.2 Introduction to the Related-Samples t Test

10.3 Computing the Related-Samples t Test

10.4 Measuring Effect Size for the Related-Samples t Test

10.5 Confidence Intervals for the Related-Samples t Test

10.6 Inferring Significance and Effect Size From a Confidence Interval

10.7 SPSS in Focus: Related-Samples t Test and Confidence Intervals

10.8 APA in Focus: Reporting the t Statistic and Confidence Intervals

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

PART IV: MAKING INFERENCES ABOUT THE VARIABILITY OF TWO OR MORE MEANS

Chapter 11: One-Way Analysis of Variance: Between- Subjects and Within- Subjects (Repeated- Measures) Designs

11.1 An Introduction to Analysis of Variance

11.2 The Between-Subjects Design for Analysis of Variance

11.3 Computing the One-Way Between-Subjects ANOVA

11.4 Post Hoc Tests: An Example Using Tukey’s HSD

11.5 SPSS in Focus: The One-Way Between-Subjects ANOVA

11.6 The Within-Subjects Design for Analysis of Variance

11.7 Computing the One-Way Within-Subjects ANOVA

11.8 Post Hoc Tests for the Within-Subjects Design

11.9 SPSS in Focus: The One-Way Within-Subjects ANOVA

11.10 A Comparison of Within-Subjects and Between-Subjects Designs for ANOVA: Implications for Power

11.11 APA in Focus: Reporting the Results of the One-Way ANOVAs

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

Chapter 12: Two-Way Analysis of Variance: Between-Subjects Factorial Design

12.1 Introduction to Factorial Designs

12.2 Structure and Notation for the Two-Way ANOVA

12.3 Describing Variability: Main Effects and Interactions

12.4 Computing the Two-Way Between-Subjects ANOVA

12.5 Analyzing Main Effects and Interactions

12.6 Measuring Effect Size for Main Effects and the Interaction

12.7 SPSS in Focus: The Two-Way Between-Subjects ANOVA

12.8 APA in Focus: Reporting the Results of the Two-Way ANOVAs

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

PART V: MAKING INFERENCES ABOUT PATTERNS, PREDICTION, AND NONPARAMETRIC TESTS

Chapter 13: Correlation and Linear Regression

13.1 The Structure of Data Used for Identifying Patterns and Making Predictions

13.2 Fundamentals of the Correlation

13.3 The Pearson Correlation Coefficient

13.4 SPSS in Focus: Pearson Correlation Coefficient

13.5 Assumptions and Limitations for Linear Correlations

13.6 Alternatives to Pearson: Spearman, Point-Biserial, and Phi

13.7 SPSS in Focus: Computing the Alternatives to Pearson

13.8 Fundamentals of Linear Regression

13.9 Using the Method of Least Squares to Find the Regression Line

13.10 Using Analysis of Regression to Determine Significance

13.11 SPSS in Focus: Analysis of Regression

13.12 A Look Ahead to Multiple Regression

13.13 APA in Focus: Reporting Correlations and Linear Regression

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

Chapter 14: Chi-Square Tests: Goodness of Fit and the Test for Independence

14.1 Distinguishing Parametric and Nonparametric Tests

14.2 The Chi-Square Goodness-of-Fit Test

14.3 SPSS in Focus: The Chi-Square Goodness-of-Fit Test

14.4 Interpreting the Chi-Square Goodness-of-Fit Test

14.5 The Chi-Square Test for Independence

14.6 Measures of Effect Size for the Chi-Square Test for Independence

14.7 SPSS in Focus: The Chi-Square Test for Independence

14.8 APA in Focus: Reporting the Chi-Square Tests

Chapter Summary Organized by Learning Objective

Key Terms

End-of-Chapter Problems

Afterword: A Final Thought on the Role of Statistics in Research Methods

Appendix A: Basic Math Review and Summation Notation

A.1 Positive and Negative Numbers

A.2 Addition

A.3 Subtraction

A.4 Multiplication

A.5 Division

A.6 Fractions

A.7 Decimals and Percents

A.8 Exponents and Roots

A.9 Order of Computation

A.10 Equations: Solving for x

A.11 Summation Notation

Key Terms

Review Problems

Appendix B. SPSS General Instructions Guide

Appendix C. Statistical Tables

Table C.1 The Unit Normal Table

Table C.2 Critical Values for the t Distribution

Table C.3 Critical Values for the F Distribution

Table C.4 The Studentized Range Statistic (q)

Table C.5 Critical Values for the Pearson Correlation

Table C.6 Critical Values for the Spearman Correlation

Table C.7 Critical Values for Chi-Square (c2)

Appendix D: Solutions for Even-Numbered Problems

Glossary

References

Index

Supplements

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Key features

NEW TO THIS EDITION:

New illustrations and a full-color design offer visual appeal and a lively presentation.
New chapter-opening vignettes ensure easier transitions between chapters and clarify core content.
New practice exercises place statistical analysis in the context of current scholarship.
Updated learning objectives and chapter summaries improve chapter organization and help students retain important information.
Updated figures and tables clarify key concepts.
A new Appendix B connects each SPSS in Focus section to the page number where it can be found in the book and provides a general instruction guide for using SPSS.
All SPSS screenshots were updated for version 24 of SPSS.
SAGE coursepacks allows instructors to import high-quality content into their school’s learning management system (LMS) with no access codes.
Guides for SPSS, R, SAS, and Stata provide even more opportunities for review, practice, and mastery of concepts.

KEY FEATURES:

A conversational writing style empowers students to view statistics as something they are capable of understanding and using.
All “by hand” calculations are also shown in SPSS to show how values in the formulas are computed and displayed in SPSS.
Making Sense sections break down the statistical concepts students typically find most challenging, review important material, and help students make sense of it.
SPSS in Focus sections provide step-by-step, classroom-tested instruction using practical research examples of how chapter concepts can be applied using SPSS.
APA in Focus sections explain how to summarize statistical results for each inferential statistic taught and how to read and report statistical results in research journals that follow APA style.
Research in Focus sections provide context by reviewing pertinent, current research that clarifies or illustrates important statistical concepts discussed in the chapter.
Current research examples, often based on data from published research, allow students to see the types of questions that behavioral researchers ask while learning about the statistics researchers use to answer them.
Learning Checks and Marginal Notes support a deeper understanding of the material.
Robust pedagogy, including step-by-step example problems, checkpoints for comprehension, bolded, boxed, and defined key terms, a comprehensive suite of end-of-chapter problems, and a mathematics primer in an appendix, help students master key concepts and skills.
Chapter-ending review problems, categorized as Factual Problems, Concept and Application Problems, and Problems in Research, allow instructors to easily identify and specifically test the type of knowledge they want to assess.
SAGE edge provides students helpful study tools, including eFlashcards, practice quizzes, and more, in one easy-to-use online environment.