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Statistics for the Social Sciences 3ed

Statistics for the Social Sciences 3ed

ISBN 9781412905466
Edition 3
Publication Date
Publisher SAGE Publications, Inc
Author(s)
Overview
Do your students lack confidence in their ability to handle quantitative work? Are they unsure about how best to use SAS, SPSS, and Excel programs? The new edition of the bestselling textbook Statistics for the Social Sciences is the solution. The previous editions of this book were popular with instructors because they helped build students' confidence and ability in doing statistical analysis, by slowly moving from concepts that require little computational work to those that require more. In this new edition, author R. Mark Sirkin demonstrates how statistics can be used so that the students come to appreciate their usefulness rather than fearing them.Key Features of the Third Edition:- An emphasis on the analysis and interpretation of data giving students a feel for how data interpretation is related to the methods by which the data was obtained- A wide range of examples from various fields in the social sciences demonstrate the role of statistical analysis in the research process- Coverage of the scientific method and how each statistical technique relates to the larger field of research - Emphasis on the interpretation of tables helping students master a topic that often proves challenging- Plenty of exercises are provided at the end of chapters so that students can practise all the statistical procedures covered- Answers to selected questions appear at the end of the book with complete worked-out solutions- Additional exercises have been added to reflect the additional computer coverage- User-friendly ways of navigating the text - key concepts are introduced and highlighted within the text, with definitions provided in boxes at the foot of each page- A handy glossary of all the the key concepts and terms in provided at the back of the book as an aid to revision- New tools to teach students how to do analysis not only through SAS and SPSS, but also using Excel descriptive statistics featuresThis book will be invaluable for upper level undergraduate students and graduate students across the social sciences. An Instructor's CD-ROM containing data sets, Powerpoint slides, exercises and answers will be available free-of-charge to professors adopting this text.Table of Contents: 1. How We Reason KEY CONCEPTS PROLOGUE AND INTRODUCTION SETTING THE STAGE SCIENCE THE SCIENTIFIC METHOD TESTING HYPOTHESES FROM HYPOTHESES TO THEORIES TYPES OF RELATIONSHIPS ASSOCIATION AND CAUSATION THE UNIT OF ANALYSIS CONCLUSION EXERCISES 2. Levels of Measurement and Forms of Data KEY CONCEPTS PROLOGUE AND INTRODUCTION MEASUREMENT NOMINAL LEVEL OF MEASUREMENT ORDINAL LEVEL OF MEASUREMENT LIKERT SCALES SCORES VERSUS FREQUENCIES INTERVAL AND RATIO LEVELS OF MEASUREMENT TABLES CONTAINING NOMINAL LEVEL OF MEASUREMENT CONCLUSION EXERCISES 3. Defining Variables KEY CONCEPTS PROLOGUE AND INTRODUCTION GATHERING THE DATA OPERATIONAL DEFINITIONS INDEX AND SCALE CONSTRUCTION VALIDITY RELIABILITY CONCLUSION EXERCISES 4. Measuring Central Tendency KEY CONCEPTS PROLOGUE AND INTRODUCTION CENTRAL TENDENCY THE MEAN THE MEDIAN USING CENTRAL TENDENCY THE MODE INTERPRETING GRAPHS CENTRAL TENDENCY AND LEVELS OF MEASUREMENT SKEWNESS OTHER GRAPHIC REPRESENTATIONS CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 5. Measuring Dispersion KEY CONCEPTS PROLOGUE AND INTRODUCTION VISUALIZING DISPERSION THE RANGE THE MEAN DEVIATION THE VARIANCE AND STANDARD DEVIATION THE COMPUTATIONAL FORMULAS FOR VARIANCE VARIANCE AND STANDARD DEVIATION FOR DATA IN FREQUENCY DISTRIBUTIONS CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 6. Constructing and Interpreting Contingency Tables KEY CONCEPTS PROLOGUE AND INTRODUCTION CONTINGENCY TABLES REGROUPING VARIABLES GENERATING PERCENTAGES INTERPRETING CONTROLLING FOR A THIRD VARIABLE PARTIAL TABLES CAUSAL MODELS COMPUTER APPLICATIONS CONCLUSION EXERCISES 7. Statistical Inference and Tests of Significance KEY CONCEPTS PROLOGUE AND INTRODUCTION WHAT IS STATISTICAL INFERENCE? RANDOM SAMPLES COMPARING MEANS THE TGEST STATISTIC PROBABILITIES DECISION MAKING DIRECTIONAL VERSUS NONDIRECTIONAL ALTERNATIVE HYPOTHESES (ONE-TAILED VERSUS TWO-TAILED TESTS) CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 8. Probability Distributions and One-Sample z and t Tests KEY CONCEPTS PROLOGUE AND INTRODUCTION NORMAL DISTRIBUTIONS THE ONE-SAMPLE z TEST FOR STATISTICAL SIGNIFICANCE THE CENTRAL LIMIT THEOREM THE NORMALITY ASSUMPTION THE ONE-SAMPLE t TEST DEGREES OF FREEDOM THE t TABLE AN ALTERNATIVE t FORMULA A z TEST FOR PROPORTIONS INTERVAL ESTIMATION CONFIDENCE INTERVALS FOR PROPORTIONS MORE ON PROBABILITY PERMUTATIONS AND COMBINATIONS CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 9. Two-Sample t Tests KEY CONCEPTS PROLOGUE AND INTRODUCTION INDEPENDENT SAMPLES VERSUS DEPENDENT SAMPLES THE TWO-SAMPLE t TEST FOR INDEPENDENTLY DRAWN SAMPLES ADJUSTMENTS FOR SIGMA-HAT SQUARED (^ 2) INTERPRETING A COMPUTER-GENERATED t TEST COMPUTER APPLICATIONS THE TWO-SAMPLE t TEST FOR DEPENDENT SAMPLES STATISTICAL SIGNIFICANCE VERSUS RESEARCH SIGNIFICANCE STATISTICAL POWER CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 10. One-Way Analysis of Variance KEY CONCEPTS PROLOGUE AND INTRODUCTION HOW ANALYSIS OF VARIANCE IS USED ANALYSIS OF VARIANCE IN EXPERIMENTAL SITUATIONS F – AN INTUITIVE APPROACH ANOVA TERMINOLOGY THE ANOVA PROCEDURE COMPARING F WITH t ANALYSIS OF VARIANCE WITH EXPERIMENTAL DATA POST HOC TESTING COMPUTER APPLICATIONS TWO-WAY ANALYSIS FOR VARIANCE CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 11. Measuring Association in Contingency Tables KEY CONCEPTS PROLOGUE AND INTRODUCTION MEASURES FOR TWO-BY-TWO TABLES MEASURES FOR n-BY-n CURVILINEARITY OTHER MEASURES OF ASSOCIATION INTERPRETING AN ASSOCIATION MATRIX CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 12. The Chi-Square Test KEY CONCEPTS PROLOGUE AND INTRODUCTION THE CONTEXT FOR THE CHI-SQUARE TEST OBSERVED VERSUS EXPECTED FREQUENCIES USING THE TABLE OF CRITICAL VALUE OF CHI-SQUARE CALCULATING THE CHI-SQUARE VALUE YATES' CORRECTION VALIDITY OF CHI-SQUARE DIRECTIONAL ALTERNATIVE HYPOTHESES TESTING SIGNIFICANCE OF ASSOCIATION MEASURES CHI-SQUARE AND PHI COMPUTER APPLICATIONS CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 13. Correlation and Regression Analysis KEY CONCEPTS PROLOGUE AND INTRODUCTION THE SETTING CARTESIAN COORDINATES THE CONCEPT OF LINEARITY LINEAR EQUATIONS LINEAR REGRESSION COMPUTER APPLICATIONS CORRELATION MEASURES FOR ANALYSIS OF VARIANCE CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 14. Additional Aspects of Correlation and Regression Analysis KEY CONCEPTS PROLOGUE AND INTRODUCTION STATISTICAL SIGNIFICANCE FOR r AND b SIGNIFICANCE OF r PARTIAL CORRELATIONS AND CAUSAL MODELS MULTIPLE CORRELATION AND THE COEFFICIENT OF MULTIPLE DETERMINATION MULTIPLE REGRESSION THE STANDARDIZED PARTIAL REGRESSION SLOPE USING A REGRESSION PRINTOUT STEPWISE MULTIPLE REGRESSION COMPUTER APPLICATIONS CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES Appendix 1: Proportions of Area Under Standard Normal Curve Appendix 2: Distribution of t Appendix 3: Critical Values of F for p = .05 Appendix 4: Critical Values of Chi-Square Appendix 5: Critical Values of the Correlation Coefficient Answers to Selected Exercises Index About the Author
Overview
Do your students lack confidence in their ability to handle quantitative work? Are they unsure about how best to use SAS, SPSS, and Excel programs? The new edition of the bestselling textbook Statistics for the Social Sciences is the solution. The previous editions of this book were popular with instructors because they helped build students' confidence and ability in doing statistical analysis, by slowly moving from concepts that require little computational work to those that require more. In this new edition, author R. Mark Sirkin demonstrates how statistics can be used so that the students come to appreciate their usefulness rather than fearing them.Key Features of the Third Edition:- An emphasis on the analysis and interpretation of data giving students a feel for how data interpretation is related to the methods by which the data was obtained- A wide range of examples from various fields in the social sciences demonstrate the role of statistical analysis in the research process- Coverage of the scientific method and how each statistical technique relates to the larger field of research - Emphasis on the interpretation of tables helping students master a topic that often proves challenging- Plenty of exercises are provided at the end of chapters so that students can practise all the statistical procedures covered- Answers to selected questions appear at the end of the book with complete worked-out solutions- Additional exercises have been added to reflect the additional computer coverage- User-friendly ways of navigating the text - key concepts are introduced and highlighted within the text, with definitions provided in boxes at the foot of each page- A handy glossary of all the the key concepts and terms in provided at the back of the book as an aid to revision- New tools to teach students how to do analysis not only through SAS and SPSS, but also using Excel descriptive statistics featuresThis book will be invaluable for upper level undergraduate students and graduate students across the social sciences. An Instructor's CD-ROM containing data sets, Powerpoint slides, exercises and answers will be available free-of-charge to professors adopting this text.Table of Contents: 1. How We Reason KEY CONCEPTS PROLOGUE AND INTRODUCTION SETTING THE STAGE SCIENCE THE SCIENTIFIC METHOD TESTING HYPOTHESES FROM HYPOTHESES TO THEORIES TYPES OF RELATIONSHIPS ASSOCIATION AND CAUSATION THE UNIT OF ANALYSIS CONCLUSION EXERCISES 2. Levels of Measurement and Forms of Data KEY CONCEPTS PROLOGUE AND INTRODUCTION MEASUREMENT NOMINAL LEVEL OF MEASUREMENT ORDINAL LEVEL OF MEASUREMENT LIKERT SCALES SCORES VERSUS FREQUENCIES INTERVAL AND RATIO LEVELS OF MEASUREMENT TABLES CONTAINING NOMINAL LEVEL OF MEASUREMENT CONCLUSION EXERCISES 3. Defining Variables KEY CONCEPTS PROLOGUE AND INTRODUCTION GATHERING THE DATA OPERATIONAL DEFINITIONS INDEX AND SCALE CONSTRUCTION VALIDITY RELIABILITY CONCLUSION EXERCISES 4. Measuring Central Tendency KEY CONCEPTS PROLOGUE AND INTRODUCTION CENTRAL TENDENCY THE MEAN THE MEDIAN USING CENTRAL TENDENCY THE MODE INTERPRETING GRAPHS CENTRAL TENDENCY AND LEVELS OF MEASUREMENT SKEWNESS OTHER GRAPHIC REPRESENTATIONS CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 5. Measuring Dispersion KEY CONCEPTS PROLOGUE AND INTRODUCTION VISUALIZING DISPERSION THE RANGE THE MEAN DEVIATION THE VARIANCE AND STANDARD DEVIATION THE COMPUTATIONAL FORMULAS FOR VARIANCE VARIANCE AND STANDARD DEVIATION FOR DATA IN FREQUENCY DISTRIBUTIONS CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 6. Constructing and Interpreting Contingency Tables KEY CONCEPTS PROLOGUE AND INTRODUCTION CONTINGENCY TABLES REGROUPING VARIABLES GENERATING PERCENTAGES INTERPRETING CONTROLLING FOR A THIRD VARIABLE PARTIAL TABLES CAUSAL MODELS COMPUTER APPLICATIONS CONCLUSION EXERCISES 7. Statistical Inference and Tests of Significance KEY CONCEPTS PROLOGUE AND INTRODUCTION WHAT IS STATISTICAL INFERENCE? RANDOM SAMPLES COMPARING MEANS THE TGEST STATISTIC PROBABILITIES DECISION MAKING DIRECTIONAL VERSUS NONDIRECTIONAL ALTERNATIVE HYPOTHESES (ONE-TAILED VERSUS TWO-TAILED TESTS) CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 8. Probability Distributions and One-Sample z and t Tests KEY CONCEPTS PROLOGUE AND INTRODUCTION NORMAL DISTRIBUTIONS THE ONE-SAMPLE z TEST FOR STATISTICAL SIGNIFICANCE THE CENTRAL LIMIT THEOREM THE NORMALITY ASSUMPTION THE ONE-SAMPLE t TEST DEGREES OF FREEDOM THE t TABLE AN ALTERNATIVE t FORMULA A z TEST FOR PROPORTIONS INTERVAL ESTIMATION CONFIDENCE INTERVALS FOR PROPORTIONS MORE ON PROBABILITY PERMUTATIONS AND COMBINATIONS CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 9. Two-Sample t Tests KEY CONCEPTS PROLOGUE AND INTRODUCTION INDEPENDENT SAMPLES VERSUS DEPENDENT SAMPLES THE TWO-SAMPLE t TEST FOR INDEPENDENTLY DRAWN SAMPLES ADJUSTMENTS FOR SIGMA-HAT SQUARED (^ 2) INTERPRETING A COMPUTER-GENERATED t TEST COMPUTER APPLICATIONS THE TWO-SAMPLE t TEST FOR DEPENDENT SAMPLES STATISTICAL SIGNIFICANCE VERSUS RESEARCH SIGNIFICANCE STATISTICAL POWER CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 10. One-Way Analysis of Variance KEY CONCEPTS PROLOGUE AND INTRODUCTION HOW ANALYSIS OF VARIANCE IS USED ANALYSIS OF VARIANCE IN EXPERIMENTAL SITUATIONS F – AN INTUITIVE APPROACH ANOVA TERMINOLOGY THE ANOVA PROCEDURE COMPARING F WITH t ANALYSIS OF VARIANCE WITH EXPERIMENTAL DATA POST HOC TESTING COMPUTER APPLICATIONS TWO-WAY ANALYSIS FOR VARIANCE CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 11. Measuring Association in Contingency Tables KEY CONCEPTS PROLOGUE AND INTRODUCTION MEASURES FOR TWO-BY-TWO TABLES MEASURES FOR n-BY-n CURVILINEARITY OTHER MEASURES OF ASSOCIATION INTERPRETING AN ASSOCIATION MATRIX CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 12. The Chi-Square Test KEY CONCEPTS PROLOGUE AND INTRODUCTION THE CONTEXT FOR THE CHI-SQUARE TEST OBSERVED VERSUS EXPECTED FREQUENCIES USING THE TABLE OF CRITICAL VALUE OF CHI-SQUARE CALCULATING THE CHI-SQUARE VALUE YATES' CORRECTION VALIDITY OF CHI-SQUARE DIRECTIONAL ALTERNATIVE HYPOTHESES TESTING SIGNIFICANCE OF ASSOCIATION MEASURES CHI-SQUARE AND PHI COMPUTER APPLICATIONS CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 13. Correlation and Regression Analysis KEY CONCEPTS PROLOGUE AND INTRODUCTION THE SETTING CARTESIAN COORDINATES THE CONCEPT OF LINEARITY LINEAR EQUATIONS LINEAR REGRESSION COMPUTER APPLICATIONS CORRELATION MEASURES FOR ANALYSIS OF VARIANCE CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES 14. Additional Aspects of Correlation and Regression Analysis KEY CONCEPTS PROLOGUE AND INTRODUCTION STATISTICAL SIGNIFICANCE FOR r AND b SIGNIFICANCE OF r PARTIAL CORRELATIONS AND CAUSAL MODELS MULTIPLE CORRELATION AND THE COEFFICIENT OF MULTIPLE DETERMINATION MULTIPLE REGRESSION THE STANDARDIZED PARTIAL REGRESSION SLOPE USING A REGRESSION PRINTOUT STEPWISE MULTIPLE REGRESSION COMPUTER APPLICATIONS CONCLUSION SUMMARY OF MAJOR FORMULAS EXERCISES Appendix 1: Proportions of Area Under Standard Normal Curve Appendix 2: Distribution of t Appendix 3: Critical Values of F for p = .05 Appendix 4: Critical Values of Chi-Square Appendix 5: Critical Values of the Correlation Coefficient Answers to Selected Exercises Index About the Author

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