David De Vaus is Associate Professor of Sociology at La Trobe University, Melbourne. He is the author of Surveys in Social Research and Research Design in Social Research. He is an international authority in the field of social research.

• PART ONE: HOW TO PREPARE DATA FOR ANALYSISHow to Code DataHow to Code Questions with Multiple AnswersCan the Respondent′s Answers be Relied on?How to Check that the Right Thing is Being MeasuredTWO: HOW TO PREPARE VARIABLES FOR ANALYSISHow to Deal with Variables with Lots of Categories How to Identify and Change the Level of Measurement of VariablesHow to Deal with Questions that Fail to Identify Real Differences Between CasesHow to Rearrange the Categories of a VariableWhat to do with Gaps in the DataWhat to do with People who ′Don′t Know′, ′Have no Opinion′ or ′Can′t Decide′How to Tell if the Distribution is NormalHow to Tell if the Relationship is LinearHow to Tell if Outlier Cases are a ProblemWhat to do if the Required Variable is not AvailableHow to Compare Apples with OrangesComparing Scores on Different VariablesPART THREE: HOW TO REDUCE THE AMOUNT OF DATA TO ANALYSEHow to Work Out Which Variables to UseHow to Combine Information from a Set of Variables into a Single MeasureHow to Build a Good Likert ScaleHow to Build a Scale Using Factor AnalysisPART FOUR: HOW AND WHEN TO GENERALISEWhat Does it Mean to Generalize?How to Judge the Extent and Effect of Sample BiasHow to Weight Samples to Adjust for BiasWhat are Tests of Significance?Should Tests of Significance be Used?What Factors Affect Significance Levels?Is the Sample Large Enough to Achieve Statistical Significance?Should Confidence Intervals be Used?PART FIVE: HOW TO ANALYSE A SINGLE VARIABLEHow to Use Tables Effectively to Display the Distribution of a Single VariableHow to Use Graphs for Single VariablesWhich Summary Statistics to Use to Describe a Single VariableWhich Statistics to Use to Generalise about a Single VariablePART SIX: HOW TO ANALYSE TWO VARIABLESHow and When to Use CrosstabulationsWhich Graph to UseHow to Narrow down the Choice When Selecting Summary StatisticsHow to Interpret a Correlation CoefficientWhich Correlation?How much Impact Does a Variable Have?How to Tell if Groups are DifferentWhich Test of Significance?How are Confidence Intervals used in Bivariate Analysis?PART SEVEN: HOW TO CARRY OUT MULTIVARIATE ANALYSISUnderstanding Bivariate RelationshipsThe Logic of Elaboration AnalysisUsing Conditional Tables as a Method of Elaboration AnalysisUsing Conditional Correlations for Elaboration AnalysisUsing Partial Tables as a Method of Elaboration AnalysisUsing Partial Correlations for Elaboration AnalysisWhat Type of Data are Needed for Multiple Regression?How to do a Multiple RegressionHow to Use Non-interval Variables in Multiple RegressionWhat Does the Multiple Regression Output Mean?What Other Multivariate Methods are Availabe?

This text will be adopted for the next academic year and the foreseeable future. The book is very well written and at a level that students on non mathematics/statistics courses can understand. Many of the issues that this text addresses are the ones that I encounter on a day-to-day basis when students consult me with their data analysis problems. For example, dealing with outliers, missing data and non-normally distributed distributions. I particularly like the way the chapter headings are stated as questions and that each chapter is relatively short. These features should reduce student anxiety, which is known to be an important issue for most students learning statistics.

David De Vaus is Associate Professor of Sociology at La Trobe University, Melbourne. He is the author of Surveys in Social Research and Research Design in Social Research. He is an international authority in the field of social research.

• PART ONE: HOW TO PREPARE DATA FOR ANALYSISHow to Code DataHow to Code Questions with Multiple AnswersCan the Respondent′s Answers be Relied on?How to Check that the Right Thing is Being MeasuredTWO: HOW TO PREPARE VARIABLES FOR ANALYSISHow to Deal with Variables with Lots of Categories How to Identify and Change the Level of Measurement of VariablesHow to Deal with Questions that Fail to Identify Real Differences Between CasesHow to Rearrange the Categories of a VariableWhat to do with Gaps in the DataWhat to do with People who ′Don′t Know′, ′Have no Opinion′ or ′Can′t Decide′How to Tell if the Distribution is NormalHow to Tell if the Relationship is LinearHow to Tell if Outlier Cases are a ProblemWhat to do if the Required Variable is not AvailableHow to Compare Apples with OrangesComparing Scores on Different VariablesPART THREE: HOW TO REDUCE THE AMOUNT OF DATA TO ANALYSEHow to Work Out Which Variables to UseHow to Combine Information from a Set of Variables into a Single MeasureHow to Build a Good Likert ScaleHow to Build a Scale Using Factor AnalysisPART FOUR: HOW AND WHEN TO GENERALISEWhat Does it Mean to Generalize?How to Judge the Extent and Effect of Sample BiasHow to Weight Samples to Adjust for BiasWhat are Tests of Significance?Should Tests of Significance be Used?What Factors Affect Significance Levels?Is the Sample Large Enough to Achieve Statistical Significance?Should Confidence Intervals be Used?PART FIVE: HOW TO ANALYSE A SINGLE VARIABLEHow to Use Tables Effectively to Display the Distribution of a Single VariableHow to Use Graphs for Single VariablesWhich Summary Statistics to Use to Describe a Single VariableWhich Statistics to Use to Generalise about a Single VariablePART SIX: HOW TO ANALYSE TWO VARIABLESHow and When to Use CrosstabulationsWhich Graph to UseHow to Narrow down the Choice When Selecting Summary StatisticsHow to Interpret a Correlation CoefficientWhich Correlation?How much Impact Does a Variable Have?How to Tell if Groups are DifferentWhich Test of Significance?How are Confidence Intervals used in Bivariate Analysis?PART SEVEN: HOW TO CARRY OUT MULTIVARIATE ANALYSISUnderstanding Bivariate RelationshipsThe Logic of Elaboration AnalysisUsing Conditional Tables as a Method of Elaboration AnalysisUsing Conditional Correlations for Elaboration AnalysisUsing Partial Tables as a Method of Elaboration AnalysisUsing Partial Correlations for Elaboration AnalysisWhat Type of Data are Needed for Multiple Regression?How to do a Multiple RegressionHow to Use Non-interval Variables in Multiple RegressionWhat Does the Multiple Regression Output Mean?What Other Multivariate Methods are Availabe?

This text will be adopted for the next academic year and the foreseeable future. The book is very well written and at a level that students on non mathematics/statistics courses can understand. Many of the issues that this text addresses are the ones that I encounter on a day-to-day basis when students consult me with their data analysis problems. For example, dealing with outliers, missing data and non-normally distributed distributions. I particularly like the way the chapter headings are stated as questions and that each chapter is relatively short. These features should reduce student anxiety, which is known to be an important issue for most students learning statistics.

David De Vaus is Associate Professor of Sociology at La Trobe University, Melbourne. He is the author of Surveys in Social Research and Research Design in Social Research. He is an international authority in the field of social research.

• PART ONE: HOW TO PREPARE DATA FOR ANALYSISHow to Code DataHow to Code Questions with Multiple AnswersCan the Respondent′s Answers be Relied on?How to Check that the Right Thing is Being MeasuredTWO: HOW TO PREPARE VARIABLES FOR ANALYSISHow to Deal with Variables with Lots of Categories How to Identify and Change the Level of Measurement of VariablesHow to Deal with Questions that Fail to Identify Real Differences Between CasesHow to Rearrange the Categories of a VariableWhat to do with Gaps in the DataWhat to do with People who ′Don′t Know′, ′Have no Opinion′ or ′Can′t Decide′How to Tell if the Distribution is NormalHow to Tell if the Relationship is LinearHow to Tell if Outlier Cases are a ProblemWhat to do if the Required Variable is not AvailableHow to Compare Apples with OrangesComparing Scores on Different VariablesPART THREE: HOW TO REDUCE THE AMOUNT OF DATA TO ANALYSEHow to Work Out Which Variables to UseHow to Combine Information from a Set of Variables into a Single MeasureHow to Build a Good Likert ScaleHow to Build a Scale Using Factor AnalysisPART FOUR: HOW AND WHEN TO GENERALISEWhat Does it Mean to Generalize?How to Judge the Extent and Effect of Sample BiasHow to Weight Samples to Adjust for BiasWhat are Tests of Significance?Should Tests of Significance be Used?What Factors Affect Significance Levels?Is the Sample Large Enough to Achieve Statistical Significance?Should Confidence Intervals be Used?PART FIVE: HOW TO ANALYSE A SINGLE VARIABLEHow to Use Tables Effectively to Display the Distribution of a Single VariableHow to Use Graphs for Single VariablesWhich Summary Statistics to Use to Describe a Single VariableWhich Statistics to Use to Generalise about a Single VariablePART SIX: HOW TO ANALYSE TWO VARIABLESHow and When to Use CrosstabulationsWhich Graph to UseHow to Narrow down the Choice When Selecting Summary StatisticsHow to Interpret a Correlation CoefficientWhich Correlation?How much Impact Does a Variable Have?How to Tell if Groups are DifferentWhich Test of Significance?How are Confidence Intervals used in Bivariate Analysis?PART SEVEN: HOW TO CARRY OUT MULTIVARIATE ANALYSISUnderstanding Bivariate RelationshipsThe Logic of Elaboration AnalysisUsing Conditional Tables as a Method of Elaboration AnalysisUsing Conditional Correlations for Elaboration AnalysisUsing Partial Tables as a Method of Elaboration AnalysisUsing Partial Correlations for Elaboration AnalysisWhat Type of Data are Needed for Multiple Regression?How to do a Multiple RegressionHow to Use Non-interval Variables in Multiple RegressionWhat Does the Multiple Regression Output Mean?What Other Multivariate Methods are Availabe?

This text will be adopted for the next academic year and the foreseeable future. The book is very well written and at a level that students on non mathematics/statistics courses can understand. Many of the issues that this text addresses are the ones that I encounter on a day-to-day basis when students consult me with their data analysis problems. For example, dealing with outliers, missing data and non-normally distributed distributions. I particularly like the way the chapter headings are stated as questions and that each chapter is relatively short. These features should reduce student anxiety, which is known to be an important issue for most students learning statistics.