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. INDICE: Part I: Introduction and Descriptive StatisticsChapter 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 VariablesChapter 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 ChartsChapter 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 ModeChapter 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 DeviationPart II: Probability and the Foundations of Inferential StatisticsChapter 5: Probability, the 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 ScoresChapter 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 DistributionsChapter 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 SizePart III: Making Inferences About One or Two MeansChapter 8: 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 IntervalsChapter 9: 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 IntervalsChapter 10: Related Samples t-Test With Confidence Intervals Related and Independent Samples Repeated-Measures 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 IntervalsPart IV: Making Inferences About The Variability of Two or More MeansChapter 11: One-Way Analysis of Variance: Between-Subjects and Within-Subjects (Repeated Measures) Designs 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 ANOVAsChapter 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 ANOVAsPart V: Making Inferences About Patterns, Prediction, and Nonparametric TestsChapter 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 RegressionChapter 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 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 Statistical Notation Appendix B: Statistical Tables Appendix C: Chapter Solutions for Even-Numbered Problems
- ISBN: 978-1-4833-5300-5
- Editorial: SAGE Publications, Inc
- Encuadernacion: Rústica
- Páginas: 576
- Fecha Publicación: 31/03/2015
- Nº Volúmenes: 1
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