## 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 |

### Što ljudi govore - Napišite recenziju

### Sadržaj

10 | |

17 | |

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

How to Prepare Variables for Analysis | 33 |

Measurement of Variables | 40 |

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

How to Rearrange the Categories of a Variable | 54 |

What to do with Gaps in the Data | 64 |

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 |

How to Narrow down the Choice When | 265 |

Which Correlation? | 274 |

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

How to Tell if the Relationship is Linear | 82 |

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 |

Should Confidence Intervals be Used? | 187 |

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 |

Elaboration Analysis | 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 |

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 | |

### Ostala izdanja - Prikaži sve

Analyzing Social Science Data: 50 Key Problems in Data Analysis David de Vaus Ograničeni pregled - 2002 |

Analyzing Social Science Data: 50 Key Problems in Data Analysis David de Vaus Pregled nije dostupan - 2002 |

### Uobičajeni izrazi i fraze

### Reference za ovu knjigu

Statistical Modelling for Social Researchers: Principles and Practice Roger Tarling Pregled nije dostupan - 2009 |