| Description |
xxiv, 401 pages : illustrations ; 24 cm |
| Contents |
Pt. 1. How to Prepare Data for Analysis -- 1. How to Code Data -- 2. How to Code Questions with Multiple Answers -- 3. Can the Respondent's Answers be Relied on? -- 4. How to Check that the Right Thing is being Measured -- Pt. 2. How to Prepare Variables for Analysis -- 5. How to Deal with Variables with Lots of Categories -- 6. How to Identify and Change the Level of Measurement of Variables -- 7. How to Deal with Questions that Fail to Identify Real Differences Between Cases -- 8. How to Rearrange the Categories of a Variable -- 9. What to do with Gaps in the Data -- 10. What to do with People who 'Don't Know', 'Have no Opinion' or 'Can't Decide' -- 11. How to Tell if the Distribution is Normal -- 12. How to Tell if the Relationship is Linear -- 13. How to Tell if Outlier Cases are a Problem -- 14. What to do if the Required Variable is not Available -- 15. How to Compare Apples with Oranges: Comparing Scores on Different Variables -- Pt. 3. How to Reduce the Amount to Data to Analyse -- 16. How to Work Out which Variables to Use -- 17. How to Combine Information from a Set of Variables into a Single Measure -- 18. How to Build a Good Likert Scale -- 19. How to Build a Scale Using Factor Analysis -- Pt. 4. How and When to Generalize -- 20. What does it Mean to Generalize? -- 21. How to Judge the Extent and Effect of Sample Bias -- 22. How to Weight Samples to Adjust for Bias -- 23. What are Tests of Significance? -- 24. Should Tests of Significance be Used? -- 25. What Factors Affect Significance Levels? -- 26. Is the Sample Large Enough to Achieve Statistical Significance? -- 27. Should Confidence Intervals be Used? -- Pt. 5. How to Analyse a Single Variable -- 28. How to Use Tables Effectively to Display the Distribution of a Single Variable -- 29. How to Use Graphs for Single Variables -- 30. Which Summary Statistics to Use to Describe a Single Variable -- 31. Which Statistic to Use to Generalize about a Single Variable? -- Pt. 6. How to Analyse Two Variables -- 32. How and When to Use Crosstabulations -- 33. Which Graph to Use -- 34. How to Narrow down the Choice When Selecting Summary Statistics -- 35. How to Interpret a Correlation Coefficient -- 36. Which Correlation? -- 37. How much Impact does a Variable have? -- 38. How to Tell if Groups are Different -- 39. Which Test of Significance? -- 40. How are Confidence Intervals used in Bivariate Analysis? -- Pt. 7. How to Carry out Multivariate Analysis -- 41. Understanding Bivariate Relationships: The Logic of Elaboration Analysis -- 42. Using Conditional Tables as a Method of Elaboration Analysis -- 43. Using Conditional Correlations for Elaboration Analysis -- 44. Using Partial Tables as a Method of Elaboration Analysis -- 45. Using Partial Correlations for Elaboration Analysis -- 46. What Type of Data are Needed for Multiple Regression? -- 47. How to do a Multiple Regression -- 48. How to Use Non-interval Variables in Multiple Regression -- 49. What does the Multiple Regression Output Mean? -- 50. What Other Multivariate Methods are Available? |
| Summary |
Analyzing Social Science Data guides students in: problems with the initial data; problems with the initial variables; how to handle too much data; how to generalize; problems of analyzing single variables; problems examining bivariate relationships; and problems examining multivariate relationships. [from publisher's advertisement] |
| Bibliography |
Includes bibliographical references (pages [391]-392) and index |
| SUBJECT |
Studies and reports. Series N, (Statistics) http://id.loc.gov/authorities/names/no99029913
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| Subject |
Social sciences -- Methodology.
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Social surveys.
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Social sciences -- Data processing.
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System analysis -- Data processing.
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Statistics.
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Social sciences -- Statistical methods.
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| LC no. |
2003268129 |
| ISBN |
0761959386 paperback |
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0761959378 |
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