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Klappentext Statistics for Research in Psychology offers an intuitive approach to statistics based on estimation for interpreting research in psychology. Zusammenfassung Statistics for Research in Psychology offers an intuitive approach to statistics based on estimation for interpreting research in psychology. Inhaltsverzeichnis Preface Acknowledgments About the Author PART I ¿ INTRODUCTION TO STATISTICS AND STATISTICAL DISTRIBUTIONS Chapter 1 ¿ Basic Concepts Statistics in Psychology Variables, Values, and Scores Measurement Populations and Samples Sampling, Sampling Bias, and Sampling Error A Preview of What's Ahead Summary Key Terms Exercises Appendix 1.1: Introduction to Excel Appendix 1.2: Introduction to SPSS Appendix 1.3: An Introduction to R Chapter 2 ¿ Distributions of Scores Introduction Distributions of Qualitative Variables Distributions of Discrete Quantitative Variables Distributions of Continuous Variables Probability Probability Distributions Summary Key Terms Exercises Appendix 2.1: Grouped Frequency Tables and Histograms in Excel Appendix 2.2: Grouped Frequency Tables and Histograms in SPSS Chapter 3 ¿ Properties of Distributions Introduction Central Tendency Dispersion (Spread) Shape Summary Key Terms Exercises Appendix 3.1: Basic Statistics in Excel Appendix 3.2: Basic Statistics in SPSS Chapter 4 ¿ Normal Distributions Introduction Normal Distributions The Standard Normal Distribution: z-Scores Area-Under-the-Curve Problems: Approximate Solutions The z-Table Area-Under-the-Curve Problems: Exact Solutions Critical Value Problems Applications Summary Key Terms Exercises Appendix 4.1: NORM.DIST and Related Functions in Excel Chapter 5 ¿ Distributions of Statistics Introduction The Distribution of Sample Means Area-Under-the-Curve Questions Critical Value Problems The Distribution of Sample Variances Summary Key Terms Exercises Appendix 5.1: Statistical Distribution Functions in Excel PART II ¿ ESTIMATION AND SIGNIFICANCE TESTS (ONE SAMPLE) Chapter 6 ¿ Estimating the Population Mean When the Population Standard Deviation Is Known Introduction An Example Point Estimates Versus Interval Estimates 95% Confidence Intervals (1-a)100% Confidence Intervals Cautions About Interpretation Estimating µ When Sample Size Is Large Assumptions Planning a Study A Word About Jerzy Neyman Summary Key Terms Exercises Appendix 6.1: Computing Confidence Intervals in Excel Chapter 7 ¿ Significance Tests Introduction A Scenario: Whole Language Versus Phonics Significance Tests Computing Exact p-Values: Directional and Non-directional Tests The Alternative Hypothesis p-Values Are Conditional Probabilities Using s to Estimate s (An Approximate z-Test) Statistical Significance Versus Practical Significance Review of Significance Tests Summary Key Terms Exercises Appendix 7.1: Significance Tests in Excel Chapter 8 ¿ Decisions, Power, Effect Size, and the Hybrid Model Introduction Statistical Decisions Neyman and Pearson The Determinants of Power Prospective Power Analysis: Planning Experiments Interpreting Effect Size The Hybrid Model: Null Hypothesis Significance Testing Summary Key Terms Exercises Chapter 9 ¿ Significance Tests: Problems and Alternatives Introduction Significance Tests Under Fire Criticisms of Significance Tests Confidence Intervals Estimating µ1 - µ0 Estimating d = (µ1 - µ0)/s Estimation Versus Significance Testing Summary Key Terms
