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Fundamental Statistics for the Social and Behavioral Sciences
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Fundamental Statistics for the Social and Behavioral Sciences

Second Edition
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October 2018 | 720 pages | SAGE Publications, Inc
Fundamental Statistics for the Social and Behavioral Sciences, Second Edition, places statistics within the research process, illustrating how they are used to answer questions and test ideas. Students learn not only how to calculate statistics, but also how to interpret and communicate the results of statistical analyses in light of a study’s research hypothesis. Featuring accessible writing and well-integrated research examples, the book gives students a greater understanding of how research studies are conceived, conducted, and communicated.

The Second Edition includes a new chapter on regression; covers how collected data can be organized, presented and summarized; the process of conducting statistical analyses to test research questions, hypotheses, and issues/controversies; and examines statistical procedures used in research situations that vary in the number of independent variables in the study. Every chapter includes learning checks, such as review questions and summary boxes, to reinforce the content students just learned, and exercises at the end of every chapter help assess their knowledge. 

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Chapter 1. Introduction to Statistics
1.1 What Is Statistics?  
1.2 Why Learn Statistics?  
1.3 Introduction to the Stages of the Research Process  
1.4 Plan of the Book  
1.5 Looking Ahead  
1.6 Summary  
1.7 Important Terms  
1.8 Exercises  
 
Chapter 2. Examining Data: Tables and Figures
2.1 An Example From the Research: Winning the Lottery  
2.2 Why Examine Data?  
2.3 Examining Data Using Tables  
2.4 Grouped Frequency Distribution Tables  
2.5 Examining Data Using Figures  
2.6 Examining Data: Describing Distributions  
2.7 Looking Ahead  
2.8 Summary  
2.9 Important Terms  
2.10 Formulas Introduced in This Chapter  
2.11 Using IBM® SPSS® Software  
2.12 Exercises  
 
Chapter 3. Measures of Central Tendency
3.1 An Example From the Research: The 10% Myth  
3.2 Understanding Central Tendency  
3.3 The Mode  
3.4 The Median  
3.5 The Mean  
3.6 Comparison of the Mode, Median, and Mean  
3.7 Measures of Central Tendency: Drawing Conclusions  
3.8 Looking Ahead  
3.9 Summary  
3.10 Important Terms  
3.11 Formulas Introduced in This Chapter  
3.12 Exercises  
 
Chapter 4. Measures of Variability
4.1 An Example From the Research: How Many “Sometimes” in an “Always”?  
4.2 Understanding Variability  
4.3 The Range  
4.4 The Interquartile Range  
4.5 The Variance (s2)  
4.6 The Standard Deviation (s)  
4.7 Measures of Variability for Populations  
4.8 Measures of Variability: Drawing Conclusions  
4.9 Looking Ahead  
4.10 Summary  
4.11 Important Terms  
4.12 Formulas Introduced in This Chapter  
4.13 Using SPSS  
4.14 Exercises  
 
Chapter 5. Normal Distributions
5.1 Example: SAT Scores  
5.2 Normal Distributions  
5.3 The Standard Normal Distribution  
5.4 Applying z-Scores to Normal Distributions  
5.5 Standardizing Frequency Distributions  
5.6 Looking Ahead  
5.7 Summary  
5.8 Important Terms  
5.9 Formulas Introduced in This Chapter  
5.10 Exercises  
 
Chapter 6. Probability and Introduction to Hypothesis Testing
6.1 A Brief Introduction to Probability  
6.2 Example: Making Heads or Tails of the Super Bowl  
6.3 Introduction to Hypothesis Testing  
6.4 Issues Related to Hypothesis Testing: An Introduction  
6.5 Looking Ahead  
6.6 Summary  
6.7 Important Terms  
6.8 Formulas Introduced in This Chapter  
6.9 Exercises  
 
Chapter 7. Testing One Sample Mean
7.1 An Example From the Research: Do You Read Me?  
7.2 The Sampling Distribution of the Mean  
7.3 Inferential Statistics: Testing One Sample Mean (? Known)  
7.4 A Second Example From the Research: Unique Invulnerability  
7.5 Introduction to the t-Distribution  
7.6 Inferential Statistics: Testing One Sample Mean (? Not Known)  
7.7 Factors Affecting the Decision About the Null Hypothesis  
7.8 Looking Ahead  
7.9 Summary  
7.10 Important Terms  
7.11 Formulas Introduced in This Chapter  
7.12 Using SPSS  
7.13 Exercises  
 
Chapter 8 Estimating the Mean of a Population
8.1 An Example From the Research: Salary Survey  
8.2 Introduction to the Confidence Interval for the Mean  
8.3 The Confidence Interval for the Mean (? Not Known)  
8.4 The Confidence Interval for the Mean (? Known)  
8.5 Factors Affecting the Width of the Confidence Interval for the Mean  
8.6 Interval Estimation and Hypothesis Testing  
8.7 Looking Ahead  
8.8 Summary  
8.9 Important Terms  
8.10 Formulas Introduced in This Chapter  
8.11 Using SPSS  
8.12 Exercises  
 
Chapter 9. Testing the Difference Between Two Means
9.1 An Example From the Research: You Can Just Wait  
9.2 The Sampling Distribution of the Difference  
9.3 Inferential Statistics: Testing the Difference Between Two Sample Means  
9.4 Inferential Statistics: Testing the Difference Between Two Sample Means (Unequal Sample Sizes)  
9.5 Inferential Statistics: Testing the Difference Between Paired Means  
9.6 Looking Ahead  
9.7 Summary  
9.8 Important Terms  
9.9 Formulas Introduced in This Chapter  
9.10 Using SPSS  
9.11 Exercises  
 
Chapter 10. Errors in Hypothesis Testing, Statistical Power, and Effect Size
10.1 Hypothesis Testing vs. Criminal Trials  
10.2 An Example From the Research: Truth or Consequences  
10.3 Two Errors in Hypothesis Testing: Type I and Type II Error  
10.4 Controlling Type I and Type II Error  
10.5 Measures of Effect Size  
10.6 Looking Ahead  
10.7 Summary  
10.8 Important Terms  
10.9 Formulas Introduced in This Chapter  
10.10 Exercises  
 
Chapter 11 One-Way Analysis of Variance (ANOVA)
11.1 An Example From the Research: It’s Your Move  
11.2 Introduction to Analysis of Variance (ANOVA)  
11.3 Inferential Statistics: One-Way Analysis of Variance (ANOVA)  
11.4 A Second Example: The Parking Lot Study Revisited  
11.5 Analytical Comparisons Within the One-Way ANOVA  
11.6 Looking Ahead  
11.7 Summary  
11.8 Important Terms  
11.9 Formulas Introduced in This Chapter  
11.10 Using SPSS  
11.11 Exercises  
 
Chapter 12. Two-Way Analysis of Variance (ANOVA)
12.1 An Example From the Research: Vote—or Else!  
12.2 Introduction to Factorial Research Designs  
12.3 The Two-Factor (A × B) Research Design  
12.4 Introduction to Analysis of Variance (ANOVA) for the Two-Factor Research Design  
12.5 Inferential Statistics: Two-Way Analysis of Variance (ANOVA)  
12.6 Investigating a Significant A × B Interaction Effect: Analysis of Simple Effects  
12.7 Looking Ahead  
12.8 Summary  
12.9 Important Terms  
12.10 Formulas Introduced in This Chapter  
12.11 Using SPSS  
12.12 Exercises  
 
Chapter 13. Correlation
13.1 An Example From the Research: It’s good for you!  
13.2 Introduction to the Concept of Correlation  
13.3 Inferential Statistics: Pearson Correlation Coefficient  
13.4 Predicting One Variable From Another: Linear Regression  
13.5 Correlating Two Sets of Ranks: The Spearman Rank-Order Correlation  
13.6 Correlational Statistics vs. Correlational Research  
13.7 Looking Ahead  
13.8 Summary  
13.9 Important Terms  
13.10 Formulas Introduced in This Chapter  
13.11 Using SPSS  
13.12 Exercises  
 
Chapter 14. Linear Regression and Multiple Correlation
14.1 Predicting One Variable From Another: Linear Regression  
14.2 Correlation With Two or More Predictors: Introduction to Multiple Correlation and Regression  
14.3 Looking Ahead  
14.4 Summary  
14.5 Important Terms  
14.6 Formulas Introduced in This Chapter  
14.7 Using SPSS  
14.8 Exercises  
 
Chapter 15 Chi-Square
15.1 An Example From the Research (One Categorical Variable): Are You My Type?  
15.2 Introduction to the Chi-Square Statistic  
15.3 Inferential Statistic: Chi-Square Goodness-of-Fit Test  
15.4 An Example From the Research (Two Categorical Variables): Seeing Red  
15.5 Inferential Statistic: Chi-Square Test of Independence  
15.6 Parametric and Nonparametric Statistical Tests  
15.7 Looking Ahead  
15.8 Summary  
15.9 Important Terms  
15.10 Formulas Introduced in This Chapter  
15.11 Using SPSS  
15.12 Exercises  

Supplements

Instructor edge site

SAGE edge for Instructors supports your teaching by making it easy to integrate quality content and create a rich learning environment for students.

  • Test banks in Word format and ExamView provide a diverse range of pre-written options as well as the opportunity to edit any question and/or insert your own personalized questions to effectively assess students’ progress and understanding.
  • Sample course syllabi for semester and quarter courses provide suggested models for structuring your courses.
  • Editable, chapter-specific PowerPoint® slides offer complete flexibility for creating a multimedia presentation for your course. 
  • Multimedia content includes original SAGE videos featuring tutorials with author Howard T. Tokunaga that bring concepts to life and appeal to diverse learners.
  • Lecture notes summarize key concepts by chapter to help you prepare for lectures and class discussions.
  • Answers to even-numbered questions from the text help facilitate grading.
  • SPSS datasets are available for use with exercises from the text.
Student edge site

SAGE edge for Students provides a personalized approach to help students accomplish their coursework goals in an easy-to-use learning environment.

  • Mobile-friendly eFlashcards strengthen understanding of key terms and concepts. 
  • Mobile-friendly practice quizzes allow for independent assessment by students of their mastery of course material. 
  • Multimedia content includes original SAGE videos featuring tutorials with author Howard T. Tokunaga that bring concepts to life and appeal to diverse learners.
  • SPSS datasets are available for use with exercises from the text.
     

“I think this is some of the best explanation for these concepts that I have read.”

JoEllen Pederson
Longwood University

“I appreciate the structures, the simplicity in the language, the clarity and the ability to pull material that is appropriate for college level courses.”

Cristine Rego
Fleming College

“I think the author has a strong command and grasp of the material which he demonstrates by providing students with a multitude of examples and formulas that are easy to understand and broken down into digestible portions for students to absorb at their own pace. The writing style of the author is excellent…He spends a significant amount of time decomposing and deconstructing complex ideas related to the measures of central tendency for both novice and expert students of statistics in a user-friendly and approachable tone.”

Keith Feigenson
Albright College

“The writing style is nice and easy to follow.”

 
Timothy Victor
University of Pennsylvania
Key features

NEW TO THIS EDITION:

  • The new edition significantly expands the discussion of linear and multiple regression and correlation, giving regression its own separate chapter. 
  • Updated data sets and research examples, including the latest 2017 salary studies, are included.
  • Additional emphasis has been placed on "eyeballing" statistical measures like the mean and standard deviation.
  • Reorganized opening chapter outlines, reduced figure sizes, and more clearly distinguished learning checks and end-of-chapter summaries enhance the readability of the book.
  • Original SAGE videos for each chapter, featuring author Howard K. Tokunaga, bring concepts to life and appeal to diverse learners.

 KEY FEATURES: 

  • Published research examples that cover a variety of real-world issues and topics in the social and behavioral sciences illustrate the use of statistical procedures to test research hypotheses. 
  • Explicit and thorough presentation of formulas and calculations help students master key techniques and prove especially helpful to students in flipped or online classes.
  • Periodic learning checks in every chapter give students an opportunity to continually assess their understanding.
  • Screenshots of statistical calculations using IBM® SPSS® Statistics at the end of chapters help students learn to use SPSS software and interpret output. 
  • Coverage of how to present data in visual form (bar charts, line graphs, scatterplots, etc.) is included for every statistical procedure.
  • Numerous end-of-chapter exercises give faculty flexibility in assigning homework.

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