Essential Statistics for the Behavioral Sciences
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Essential Statistics for the Behavioral Sciences

Essential Statistics for the Behavioral Sciences


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About the Book

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. WebAssign® This title is available on WebAssign, allowing instructors to produce and manage assignments with their students online using a grade book that allows them to track and monitor students′ progress. Students receive unlimited practice using a combination of multiple choice and algorithmic questions, and are allowed unlimited access to this edition of the textbook in the same course at no additional cost. WebAssign provides instant feedback and links directly to the accompanying eBook section where the concept was covered, allowing students to find the correct solution.

Table of Contents:
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

About the Author :
Gregory J. Privitera is a three-time national-award-winning author and a professor of psychology at St. Bonaventure University where he is a recipient of its highest teaching honor, The Award for Professional Excellence in Teaching, and its highest honor for scholarship, The Award for Professional Excellence in Research and Publication. Dr. Privitera received his PhD in behavioral neuroscience in the field of psychology at the State University of New York at Buffalo and continued with his postdoctoral research at Arizona State University. His texts span diverse topics in psychology and the behavioral sciences and include an introductory psychology text, three statistics texts, two research methods texts, and multiple other texts bridging knowledge creation across health, health care, and analytics. In addition, Dr. Privitera has authored more than three dozen peer-reviewed papers aimed at advancing our understanding of health, health literacy, and informing policy in health care. His research has earned recognition by the American Psychological Association and in media to include Oprah’s Magazine, Time Magazine, and the Wall Street Journal. He mentors a variety of undergraduate research projects at St. Bonaventure University, where dozens of students, many of whom have gone on to earn graduate and doctoral degrees at various institutions, have coauthored and presented research work. In addition to his teaching, research, and advisement, Dr. Privitera is a veteran of the U.S. Marine Corps, is an identical twin, and is married with two daughters, Grace Ann and Charlotte Jane, and two sons, Aiden Andrew and Luca James.   

Review :
"Nice breadth of material and broken down into manageable size chapters." "It is very easy to read and comprehend." "I like the dedication to SPSS and APA style." "I was most impressed with the many pedagogical features that enhance student learning." "I really want to commend the author for the learning objectives and end of chapter problems. Great stuff! "I really like the tables and figures in this textbook! They are the BEST among those used in the elementary statistics textbooks I know."


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Product Details
  • ISBN-13: 9781483353005
  • Publisher: SAGE Publications Inc
  • Publisher Imprint: SAGE Publications Inc
  • Height: 254 mm
  • No of Pages: 576
  • Weight: 1010 gr
  • ISBN-10: 1483353001
  • Publisher Date: 19 Feb 2015
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Width: 203 mm


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