## 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. 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 The book is a "tour de force" in making data analysis manageable and rewarding for today's undergraduate studying research methods. 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' - "Alan Bryman, Professor of Social Research, Loughborough University |

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### Contents

2 | |

10 | |

17 | |

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

How to Prepare Variables for Analysis | 33 |

variable has too many categories | 34 |

How to Identify and Change the Level | 40 |

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

Should Confidence Intervals be Used? | 187 |

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 Rearrange the Categories of a Variable | 54 |

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 |

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 |

Is the Sample Large Enough to Achieve Statistical | 180 |

same parameters as Table 26 1 | 184 |

How to Narrow down the Choice When | 265 |

Which 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 Carry 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 |

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

forms of heteroscedasticity | 349 |

How to do a Multiple Regression | 353 |

How to Use Noninterval Variables in Multiple Regression | 368 |

What does the Multiple Regression Output Mean? | 374 |

What Other Multivariate Methods are Available? | 383 |

391 | |

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### References to this book

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