Analyzing quantitative data : from description to explanation / Norman Blaikie.

Format:

Book

Author/Creator:

Blaikie, Norman W. H., 1933-

Language:

English

Subjects (All):

Social sciences--Research.

Social sciences.

Physical Description:

xx, 352 pages : illustrations ; 25 cm

Place of Publication:

London : Thousand Oaks, CA : SAGE, 2003.

Summary:

This generous and insightful book is designed for social researchers who need to know what procedures to use under what circumstances, in practical research projects. It accomplishes this without requiring an in-depth understanding of statistical

Contents:

1 Social Research and Data Analysis: Demystifying Basic Concepts 10

What is the purpose of social research? 10

The research problem 11

Research objectives 11

Research questions 13

The role of hypotheses 13

What are data? 15

Data and social reality 16

Types of data 17

Forms of data 20

Concepts and variables 22

Levels of measurement 22

Categorical measurement 23

Nominal-level measurement 23

Ordinal-level measurement 23

Metric measurement 24

Interval-level measurement 25

Ratio-level measurement 25

Discrete and continuous measurement 26

Transformations between levels of measurement 27

What is data analysis? 28

Types of analysis 29

Univariate descriptive analysis 29

Bivariate descriptive analysis 29

Explanatory analysis 30

Inferential analysis 32

Logics of enquiry and data analysis 33

2 Data Analysis in Context: Working with Two Data Sets 37

Student sample 39

Resident sample 39

Concepts and variables 40

Operational definitions 40

Levels of measurement 43

Data reduction 44

3 Descriptive Analysis - Univariate: Looking for Characteristics 47

Basic mathematical language 48

Univariate descriptive analysis 51

Describing distributions 52

Frequency counts and distributions 53

Nominal categories 53

Ordinal categories 54

Discrete and grouped data 55

Proportions and percentages, ratios and rates 59

Pictorial representations 62

Categorical variables 63

Metric variables 64

Shapes of frequency distributions: symmetrical, skewed and normal 66

Measures of central tendency 68

The three Ms 68

Mode 68

Median 69

Mean 71

Mean of means 74

Comparing the mode, median and mean 75

Comparative analysis using percentages and means 76

Measures of dispersion 77

Categorical data 78

Interquartile range 78

Percentiles 79

Metric data 79

Range 79

Mean absolute deviation 79

Standard deviation 80

Variance 83

Characteristics of the normal curve 84

4 Descriptive Analysis

Bivariate: Looking for Patterns 89

Association with nominal-level and ordinal-level variables 91

Contingency tables 91

Forms of association 94

Positive and negative 94

Linear and curvilinear 96

Symmetrical and asymmetrical 96

Measures of association for categorical variables 96

Nominal-level variables 97

Contingency coefficient 97

Standardized contingency coefficient 99

Phi 101

Cramer's V 101

Ordinal-level variables 102

Gamma 102

Kendall's tau-b 104

Other methods for ranked data 105

Combinations of categorical and metric variables 105

Association with interval-level and ratio-level variables 106

Scatter diagrams 106

Covariance 107

Pearson's r 108

Comparing the measures 111

Association between categorical and metric variables 113

Code metric variable to ordinal categories 113

Dichotomize the categorical variable 113

5 Explanatory Analysis: Looking for Influences 116

The use of controlled experiments 117

Explanation in cross-sectional research 118

Bivariate analysis 120

Influence between categorical variables 120

Nominal-level variables: lambda 120

Ordinal-level variables: Somer's d 124

Influence between metric variables: bivariate regression 125

Two methods of regression analysis 128

Coefficients 130

Points to watch for 133

Influence between categorical and metric variables 134

Coding to a lower level 134

Means analysis 134

Dummy variables 135

Multivariate analysis 136

Trivariate analysis 136

Forms of relationships 136

Interacting variables 137

The logic of trivariate analysis 138

Influence between categorical variables 141

Three-way contingency tables 141

Other methods 145

Influence between metric variables 146

Partial correlation 146

Multiple regression 146

Collinearity 150

Multiple-category dummy variables 150

Other methods 153

Dependence techniques 153

Analysis of variance 154

Multiple analysis of variance 154

Logistic regression 154

Logit logistic regression 154

Multiple discriminant analysis 154

Structural equation modelling 154

Interdependence techniques 155

Factor analysis 155

Cluster analysis 155

Multidimensional scaling 155

6 Inferential Analysis: From Sample to Population 159

Sampling 160

Populations and samples 160

Probability samples 161

Probability theory 163

Sample size 166

Response rate 167

Sampling methods 168

Parametric and non-parametric tests 171

Inference in univariate descriptive analysis 172

Categorical variables 173

Metric variables 175

Inference in bivariate descriptive analysis 177

Testing statistical hypotheses 178

Null and alternative hypotheses 179

Type I and type II errors 180

One-tailed and two-tailed tests 181

The process of testing statistical hypotheses 182

Testing hypotheses under different conditions 183

Some critical issues 185

Categorical variables 189

Nominal-level data 189

Ordinal-level data 191

Metric variables 192

Comparing means 192

Group t test 193

Mann-Whitney U test 197

Analysis of variance 201

Test of significance for Pearson's r 204

Inference in explanatory analysis 205

Nominal-level data 205

Ordinal-level data 206

Metric variables 208

Bivariate regression 208

Multiple regression 209

7 Data Reduction: Preparing to Answer Research Questions 214

Scales and indexes 214

Creating scales 215

Environmental Worldview scales and subscales 215

Pre-testing the items 216

Item-to-item correlations 217

Item-to-total correlations 217

Cronbach's alpha 219

Factor analysis 220

Willingness to Act scale 238

Avoidance of environmentally damaging products 240

Support for environmental groups 240

Recycling behaviour 240

Recoding to different levels of measurement 241

Environmental Worldview scales and subscales 242

Recycling index 243

Age 243

Characteristics of the samples 244

8 Real Data Analysis: Answering Research Questions 249

Univariate descriptive analysis 249

Environmental Worldview 250

Environmentally Responsible Behaviour 252

Bivariate descriptive analysis 257

Environmental Worldview and Environmentally Responsible Behaviour 258

Metric variables 258

Categorical variables 260

Comparing metric and categorical variables 262

Age, Environmental Worldview and Environmentally Responsible Behaviour 264

Metric variables 264

Categorical variables 266

Gender, Environmental Worldview and Environmentally Responsible Behaviour 268

Explanatory analysis 270

Bivariate analysis 273

Categorical variables 274

Categorical and metric variables: means analysis 276

Metric variables 277

Multivariate analysis 277

Categorical variables 278

EWVGSC and WILLACT with ERB 279

WILLACT, Age and Gender with ERB 282

Categorical and metric variables: means analysis 285

EWVGSC and WILLACT with ERB 286

WILLACT and Gender with ERB 287

Metric variables 292

Partial correlation 292

Multiple regression 293

Appendix B Equations 326

Appendix C SPSS Procedures 333.

Notes:

Includes bibliographical references and index.

ISBN:

0761967583

0761967591

OCLC:

52288275