Gregory J. Privitera 
Essential Statistics for the Behavioral Sciences [EPUB ebook] 

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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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    €97.99
    Métodos de Pagamento

    Tabela de Conteúdo

    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

    Sobre o autor

    Gregory J. Privitera is 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 Ph D 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. He is a nationally award-winning author and research scholar. His textbooks span across diverse topics in psychology and the behavioral sciences, including an introductory psychology text, four 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 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.  
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    Língua Inglês ● Formato EPUB ● Páginas 640 ● ISBN 9781506386287 ● Tamanho do arquivo 32.1 MB ● Editora SAGE Publications ● Cidade Thousand Oaks ● País US ● Publicado 2017 ● Edição 2 ● Carregável 24 meses ● Moeda EUR ● ID 5577822 ● Proteção contra cópia Adobe DRM
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