Data analysis : an introduction
Lewis-Beck, Michael S.
Data analysis : an introduction Book - New Delhi,Los Angeles etc Sage Pub. 1995 - ix,77p.
Series Editor's Introduction vii Acknowledgments ix 1.Introduction 1 2. Data Gathering 2 The Research Question 3 The Sample 3 The Measures 4 Data Coding, Entry, and Checking 7 3. Univariate Statistics 8 Central Tendency 8 Dispersion 11 Central Tendency, Dispersion, and Outliers 16 4. Measures of Association 19 Correlation 19 Ordinal Data: The Tau Measure of Association 22 Nominal Data: Goodman and Kruskals' Lambda 26 Dichotomous Variables: Flexibility of Choice 28 Summary and Conclusion 29 5. Significance Testing 30 The Logic: A Simple Example 31 Applying the Logic: Bivariate Measures of Association 35 Critical Issues 38 Summary and Conclusion 40 6. Simple Regression 41 Y as a Function of X 41 The Least Squares Principle 43 Intercept and Slope 45 Prediction and Goodness-of-Fit 47 Significance Tests and Confidence Intervals 49 Presenting Regression Results: A Summary Guide 53 7. Multiple Regression 53 An Example 54 The Notion of Statistical Control 55 Specification Error 57 Dummy Variables 60 Collinearity 62 Interaction Effects 65 Nonlinearity 67 Summary and Conclusion 71 8. Recommendations 72 9. Appendix: The Regression Assumptions 72 References 75 About the Author 77
0803957726
001.4225 / LEW
Data analysis : an introduction Book - New Delhi,Los Angeles etc Sage Pub. 1995 - ix,77p.
Series Editor's Introduction vii Acknowledgments ix 1.Introduction 1 2. Data Gathering 2 The Research Question 3 The Sample 3 The Measures 4 Data Coding, Entry, and Checking 7 3. Univariate Statistics 8 Central Tendency 8 Dispersion 11 Central Tendency, Dispersion, and Outliers 16 4. Measures of Association 19 Correlation 19 Ordinal Data: The Tau Measure of Association 22 Nominal Data: Goodman and Kruskals' Lambda 26 Dichotomous Variables: Flexibility of Choice 28 Summary and Conclusion 29 5. Significance Testing 30 The Logic: A Simple Example 31 Applying the Logic: Bivariate Measures of Association 35 Critical Issues 38 Summary and Conclusion 40 6. Simple Regression 41 Y as a Function of X 41 The Least Squares Principle 43 Intercept and Slope 45 Prediction and Goodness-of-Fit 47 Significance Tests and Confidence Intervals 49 Presenting Regression Results: A Summary Guide 53 7. Multiple Regression 53 An Example 54 The Notion of Statistical Control 55 Specification Error 57 Dummy Variables 60 Collinearity 62 Interaction Effects 65 Nonlinearity 67 Summary and Conclusion 71 8. Recommendations 72 9. Appendix: The Regression Assumptions 72 References 75 About the Author 77
0803957726
001.4225 / LEW