## Analyzing Social Science Data: 50 Key Problems in Data AnalysisIn this novel and refreshing textbook, David de Vaus directs students to the core of data analysis. The book is an authoritative guide to the problems facing beginners in the field. The book is a `I'm full of admiration for this book. Once again, David de Vaus has come up with a superb book that is well written and organized and which will be a boon to a wide range of students. He has taken a vast array of problems that users of quantitative data analysis procedures are likely to encounter. The selection of issues and problems ... reflects the experience of a true practitioner with a grasp of his field and of the intricacies of the research process. The selection of issues clearly derives also from experience of teaching students how to do research and analyse data....A large number of practitioners will want the book. I was surprised at how much I learned from this. This will be a vital book for the bookshelves of practitioners of the craft of quantitative data analysis' - |

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something about discriminant validity and convergent validity

### Contents

How to Code Questions with Multiple Answers | 10 |

Can the Respondents Answers be Relied on? | 17 |

How to Check that the Right Tfling is being Measured | 25 |

Is the Sample Large Enough to Achieve Statistical | 26 |

How to Prepare Variables for Analysis | 33 |

How to Identify and Change the Level | 40 |

How to Deal with Questions that Fail to Identify Real | 48 |

How to Rearrange the Categories of a Variable | 54 |

How to Analyse a Single Variable | 195 |

How to Use Graphs for Single Variables | 203 |

Which Summary Statistics to Use to Describe | 218 |

Which Statistic to Use to Generalize about | 228 |

How to Analyse Two Variables | 237 |

Which Graph to Use | 246 |

exnuptial children by age group percentages | 250 |

How to Narrow down the Choice When | 265 |

What to do with Gaps in the Data | 64 |

What to do with People who Dont Know Have | 72 |

How to Tell if the Relationship is Linear | 82 |

two variables | 83 |

How to Tell if Outlier Cases are a Problem | 92 |

What to do if the Required Variable is not Available | 99 |

Comparing | 107 |

How to Reduce the Amount of Data to Analyse | 113 |

How to Build a Good Likert Scale | 124 |

How to Build a Scale Using Factor Analysis | 134 |

Part Four How and When to Generalize | 147 |

How to Weight Samples to Adjust for Bias | 160 |

What are Tests of Significance? | 166 |

What Factors Affect Significance Levels? | 175 |

using different variation assumptions | 184 |

Should Confidence Interuals be Used? | 187 |

Wftich Correlation? | 274 |

How to Tell if Groups are Different | 288 |

Which Test of Significance? | 293 |

How are Confidence Intervals used in Bivariate Analysis? | 306 |

How to Cany out Multivariate Analysis | 315 |

Using Conditional Tables as a Method | 321 |

Using Conditional Correlations for Elaboration Analysis | 328 |

Using Partial Correlations for Elaboration Analysis | 337 |

WItat Type of Data are Needed for Multiple Regression? | 343 |

How to do a Multiple Regression | 353 |

How to Use Noninterval Variables in Multiple Regression | 368 |

Wliat does the Multiple Regression Output Mean? | 374 |

Wttat Other Multivariate Methods are Available? | 383 |

391 | |

### Other editions - View all

Analyzing Social Science Data: 50 Key Problems in Data Analysis Professor David de Vaus Limited preview - 2002 |

### Common terms and phrases

### References to this book

Statistical Modelling for Social Researchers: Principles and Practice Roger Tarling No preview available - 2008 |