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Essential Statistics for the Behavioral Sciences

Essential Statistics for the Behavioral Sciences

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January 2015 | 576 pages | SAGE Publications, Inc
Employing the hallmark pedagogical support of his successful comprehensive text, award-winning author, teacher, and advisor Gregory J. Privitera offers a brief and engaging introduction to the field with Essential Statistics for the Behavioral Sciences. Practical examples, integrated SPSS® coverage and screenshots, and numerous learning tools make intimidating concepts accessible. Students will welcome Privitera's clear instruction, conversational voice, and application of statistics to current, real-life research problems.

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Bundle it with Research Methods for the Behavioral Sciences, 2e by Gregory J. Privitera and save $45.00. 
Use bundle ISBN: 978-1-5063-7377-5
Part I: Introduction and Descriptive Statistics
Chapter 1: Introduction to Statistics
The Use of Statistics in Science

Descriptive and Inferential Statistics

Research Methods and Statistics

Scales of Measurement

Types of Variables for Which Data are Measured

Research in Focus: Evaluating Data and Scales of Measurement

SPSS in Focus: Entering and Defining Variables

Chapter 2: Summarizing Data: Frequency Distributions in Tables and Graphs
Why Summarize Data?

Frequency Distributions for Grouped Data

Identifying Percentile Points and Percentile Ranks

SPSS in Focus: Frequency Distributions for Quantitative Data

Frequency Distributions for Ungrouped Data

Research in Focus: Summarizing Demographic Information

SPSS in Focus: Frequency Distribution for Categorical Data

Graphing Distributions: Continuous Data

Graphing Distributions: Discrete and Categorical Data

Research in Focus: Frequencies and Percents

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

Chapter 3: Summarizing Data: Central Tendency
Introduction to Central Tendency

Measures of Central Tendency

Characteristics of the Mean

Choosing an Appropriate Measure of Central Tendency

Research in Focus: Describing Central Tendency

SPSS in Focus: Mean, Median, and Mode

Chapter 4: Summarizing Data: Variability
Measuring Variability

Range and Interquartile Range

Research in Focus: Reporting the Range

The Variance

Explaining Variance for Populations and Samples

The Computational Formula for Variance

The Standard Deviation

What Does the Standard Deviation Tell Us?

Characteristics of the Standard Deviation

SPSS in Focus: Range, Variance, and Standard Deviation

Part II: Probability and the Foundations of Inferential Statistics
Chapter 5: Probability, Normal Distribution, and z Scores
Introduction to Probability

Calculating Probability

Probability and the Normal Distribution

Characteristics of the Normal Distribution

Research in Focus: The Statistical Norm

The Standard Normal Distribution and z Scores

A Brief Introduction to the Unit Normal Table

Locating Proportions

Locating Scores

SPSS in Focus: Converting Raw Scores to Standard z Scores

Chapter 6: Characteristics of the Sample Mean
Selecting Samples From Populations

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

Sampling Distributions: The Mean

The Standard Error of the Mean

Factors That Decrease Standard Error

SPSS in Focus: Estimating the Standard Error of the Mean

APA in Focus: Reporting the Standard Error

Standard Normal Transformations With Sampling Distributions

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

Four Steps to Hypothesis Testing

Hypothesis Testing and Sampling Distributions

Making a Decision: Types of Error

Testing Significance: Examples Using the z Test

Research in Focus: Directional Versus Nondirectional Tests

Measuring the Size of an Effect: Cohen’s d

Effect Size, Power, and Sample Size

Additional Factors That Increase Power

SPSS in Focus: A Preview for Chapters 8 to 14

APA in Focus: Reporting the Test Statistic and Effect Size

Part III: Making Inferences About One or Two Means
Chapter 8: Testing Means: One-Sample t Test With Confidence Intervals
Going From z to t

The Degrees of Freedom

Reading the t Table

Computing the One–Sample t Test

Effect Size for the One-Sample t Test

Confidence Intervals for the One-Sample t Test

Inferring Significance and Effect Size From a Confidence Interval

SPSS in Focus: One–Sample t Test and Confidence Intervals

APA in Focus: Reporting the t Statistic and Confidence Intervals

Chapter 9: Testing Means: Two-Independent-Sample t Test With Confidence Intervals
Introduction to the Between-Subjects Design

Selecting Samples for Comparing Two Groups

Variability and Comparing Differences Between Two Groups

Computing the Two-Independent–Sample t Test

Effect Size for the Two-Independent-Sample t Test

Confidence Intervals for the Two-Independent-Sample t Test

Inferring Significance and Effect Size From a Confidence Interval

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

APA in Focus: Reporting the t Statistic and Confidence Intervals

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

Introduction to the Related-Samples t Test

Computing the Related-Samples t Test

Measuring Effect Size for the Related-Samples t Test

Confidence Intervals for the Related-Samples t Test

Inferring Significance and Effect Size From a Confidence Interval

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

APA in Focus: Reporting the t Statistic and Confidence Intervals

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
An Introduction to Analysis of Variance

The Between-Subjects Design for Analysis of Variance

Computing the One-Way Between-Subjects ANOVA

Post Hoc Tests: An Example Using Tukey’s HSD

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

The Within-Subjects Design for Analysis of Variance

Computing the One-Way Within-Subjects ANOVA

Post Hoc Tests for the Within-Subjects Design

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

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

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

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

Structure and Notation for the Two-Way ANOVA

Describing Variability: Main Effects and Interactions

Computing the Two-Way Between-Subjects ANOVA

Analyzing Main Effects and Interactions

Measuring Effect Size for Main Effects and the Interaction

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

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

Part V: Making Inferences About Patterns, Prediction, and Nonparametric Tests
Chapter 13: Correlation and Linear Regression
The Structure of Data Used for Identifying Patterns and Making Predictions

Fundamentals of the Correlation

The Pearson Correlation Coefficient

SPSS in Focus: Pearson Correlation Coefficient

Assumptions and Limitations for Linear Correlations

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

SPSS in Focus; Computing the Alternatives to Pearson

Fundamentals of Linear Regression

Using the Method of Least Squares to Find the Regression Line

Using Analysis of Regression to Determine Significance

SPSS in Focus: Analysis of Regression

A Look Ahead to Multiple Regression

APA in Focus: Reporting Correlations and Linear Regression

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

The Chi-Square Goodness-of-Fit Test

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

Interpreting the Chi-Square Goodness-of-Fit Test

The Chi-Square Test for Independence

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

SPSS in Focus: The Chi-Square Test for Independence

APA in Focus: Reporting the Chi-Square Tests

Appendix A: Basic Math Review and Summation Notation

Appendix B: Statistical Tables

Appendix C: Chapter Solutions for Even-Numbered Problems



Instructor Teaching Site

SAGE edge for Instructors, a password-protected instructor resource site, supports teaching by making it easy to integrate quality content and create a rich learning environment for students. The following chapter-specific assets are available on the teaching site:

  • Test banks written by Greg Privitera provide a diverse range of questions as well as the opportunity to edit any question and/or insert personalized questions to effectively assess students’ progress and understanding
  • Lecture notes summarize key concepts by chapter to assist in the preparation of lectures and class discussions
  • Sample course syllabi for semester and quarter courses provide suggested models for structuring a course
  • Editable, chapter-specific PowerPoint slides offer complete flexibility for creating a multimedia presentation for the course
  • Answer keys for all problems featured in the book and in the SPSS Workbook assist in grading student work
  • Tables and figures from the book are provided for use in your course
  • Course cartridge for easy LMS integration is included
Student Study Site

SAGE edge for Students provides a personalized approach to help students accomplish their coursework goals in an easy-to-use learning environment. The open-access study site includes:


  • SPSS in Focus Screencasts that accompany each SPSS in Focus section from the book show you how to use SPSS step-by-step
  • A customized online action plan includes tips and feedback on progress through the course and materials, allowing students to individualize their learning experience
  • Learning objectives reinforce the most important material
  • Mobile-friendly eFlashcards strengthen understanding of key terms and concepts
  • Web resources are included for further research and insights.
  • Multimedia content includes audio and video resources that appeal to students with different learning styles
  • EXCLUSIVE! Access to full-text SAGE journal articles that have been carefully selected to support and expand on the concepts presented in each chapter

“Nice breadth of material and broken down into manageable size chapters.”

Chiara Sabina, Penn State Harrisburg

“It is very easy to read and comprehend.”

Ray Garza, Texas A&M International University

“I like the dedication to SPSS and APA style.”

Amy Cota-McKinley, Worcester State University

“I was most impressed with the many pedagogical features that enhance student learning.”

Linda J. Palm, Coastal Carolina University

“I really want to commend the author for the learning objectives and end of chapter problems. Great stuff!

Melanie Tabak, Kent State University at Trumbull

“I really like the tables and figures in this textbook! They are the BEST among those used in the elementary statistics textbooks I know.”

May Takeuchi, University of North Alabama

great little book for beginers. Also great for self study.
only anoying point is there are only answers to the even numbered questions in the book.
good review questions though.

Dr Katherine Elizabeth Bruns
Psychology, Fachhochschule des Mittelstands (FHM)
March 2, 2018

I like the text; however, I have chose to adopt "Statistics for the Behavioral Sciences 2nd Ed." and the SPSS workbook that goes with it instead.

Dr George Edward Humes
Psychology Dept, Kean University
November 13, 2016

I'm not in a position to adopt this semester. I'm reviewing this textbook for Q&A items to test out with my current Elementary Statistics students. I will continue reviewing for a Fall2016 decision. Thank you

Dr Anne Marie S. Marshall
School Of Math Natural Science, Berry College
October 30, 2015

This book is user friendly and integrates in a clear and strait forward presentation the statistical concepts any student of Social
Sciences will see throughout their undergraduate and graduate formation.

Professor Irmannette Torres-Lugo
Social Sciences, University of Puerto Rico at Cayey
July 9, 2015

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Sample Materials & Chapters

Chapter 1

Chapter 10

Gregory J. Privitera

Gregory J. Privitera is an associate professor of psychology at St. Bonaventure University. Dr. Privitera received his PhD in behavioral neuroscience in the field of psychology at the State University of New York at Buffalo. He went on to complete postdoctoral research at Arizona State University before beginning his tenure at St. Bonaventure University. He is an author of multiple books on statistics, research methods, and the psychology of eating, in addition to authoring over two-dozen peer-reviewed scientific articles aimed at advancing our understanding of health and promoting the intake of healthier diets for children and adults. He... More About Author

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