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

Includes bibliographical references (p. [344]-346) and index.

For social researchers who need to know what procedures to use under what circumstances in practical research projects, this book does not require an indepth understanding of statistical theory.

Introduction: About the Book --Why was it Written? -- Who is it for? --What makes it different --What are the controversial issues? --What is the best way to read this book? --What is needed to cope with it?--Notes-- 1. Social Research and Data Analysis: Demystifying Basic Concepts.-- Introduction--What is the purpose of social research?--The research problem--Research objectives--Research questions--The role of hypotheses--What are data?--Data and social reality--Types of data--Forms of data--Concepts and variables-- Levels of measurement--Categorical measurement--Normal-level measurement--Ordinal-level measurement--Metric measurement--Interval-level measurement--Ratio-level measurement--Discrete and continuous measuremeent--Review--Transformations between levels of measurement-- What is data analysis?--Types of analysis--Univariate descriptive analysis--Bivariate descriptive analysis--Explanatory analysis--Inferential analysis--Logics of enquiry and data analysis--Summary--Notes--2. Data analysis in Context: Working with Two Data Sets--Introduction--Two Samples---Description of the samples--Student sample--Resident sample--Concepts and variables--Formal definitions--Operational definitions--Levels of measurement--Data reduction--Notes-- 3. Descriptive Analysis:Univariate:Looking for Characteristics -- Introduction--Basic mathematical language--Univariate descriptive analysis--Describing distributions-- Frequency counts and distributions-- Nominal categories--Ordinal categories--Discrete and grouped data- Proportions and percentages,ratios and rates-Proportions--Percentages--Ratios--Rates--Pictorial representatives--Categorical variables--Metric variables--Shapes of frequency distributions: symmetrical,skewed and normal--Measures of central tendency-- The three Ms--Mode--Median--Mean--Mean of means--Comparing the mode,median and mean--Comparative anslysis using percentages and means--Measures of dispersion--Categorical data--Interquartile range--Percentiles--Metric data--Range--Mean absolute deviation--Standard deviation--Variance--Characteristics of the normal curve--Summary--Notes. 4 Descriptive Analysis - Bivariate: Looking for Patterns-- Introduction--Association with nominal-level and ordinal-level variables--Contingency tables--Forms of association--Positive and negative--Linear and curvilinear--Symmetrical and asymmetrical--Measures of association for categorical variables--Nominal-level variables--Contingency coefficient--Standardized contingency coefficient--Phi--Cramer\'s V--Ordinal-level variables--Gamma--Kendall\'s tau-b--Other methods for ranked data--Combinations of categorical and metric variables--Association with interval-level and ration-level variables--Scatter diagrams--Covariance--Pearson\'s r--Comparing the measures--Association between categorical and metric variables--Code metric variable to ordinal categories--Dichotomize the categorical variable--Summary--Notes. 5.Explanatory Analysis: Looking for Influences--Introduction--The use of controlled experiments--Explanation in cross-sectional research--Bivariate analysis--Influence between categorical variables--Nominal-level variables:lambda--Ordinal-level variables:Somer\'s d--Influence between metric variables:bivariate regression--Two methods of regression analysis--Coefficients--An example--Points to watch for--Influence between categorical and metric variables--Coding to a lower level--Means analysis--Dummy variables--Multivariate analysis--Trivariate analysis--Forms of relationships--Interacting variables--The logic of trivariate analysis--Influence between categorical variables--Three-way contingency tables--An example--Other methods--Influence between metric variables--Partial correlation--Multiple regression--An example--Collinearity--Multiple-category dummy variables--Other methods--Dependence techniques--Analysis of variance--Multiple analysis of variance--Logistic regression-- Logit logistic regression--Multiple discriminant anslysis--Structural equation modelling--Interdependence techniques--Factor analysis--Cluster analysis--Multidimensional scaling-- Summary--Notes. 6. Inferential Analysis: From Sample to Population--Introduction--Sampling--Populations and samples--Probability samples--Probability theory--Sample size--Response rate--Sampling methods--Parametric and non-parametric tests--Inference in univariate descriptive analysis--Categorical variables--Metric variables--Inference in bivariate descriptive analysis--Testing statistical hypotheses--Null and alternative hypotheses-Type 1 and type 11 errors--One-tailed and two-tailed tests--The process of testing statistical hypotheses--Testing hypotheses under different conditions--Some critical issues--Categorical variables--Nominal-level data--Ordinal-level data--Metric variables--Comparing means--Group t test--Mann-Whitney U test--Analysis of variance--Test of significance for Pearson\'s r--Inference in explanatory analysis--Nominal-level data--Ordinal-level data--Metric variables--Bivariate regression--ultiple regression--Summary--Notes--7. Data Reduction: Preparing to Answer Research Questions--Introduction--Scales and indexes--Creating scales--Environmental Worldview scales and subscales--Pre-testing the items--Item-to-item correlations--Item-to-total correlations--cronbach\'s alpha--Factor analysis--Willingness to Act scale--Indexes--Avoidance of environmentally damaging products--Support for environmental groups--Recycling behaviour--Recoding to different levels of measurement--Environmental Worldview scales and subscales--Recycling index--Age--Characteristics of the samples--Summary--Notes--8. Real Data Analysis: Answering Research Questions--Introduction--Univariate descriptive analysis--Environmental Worldview-- Environmentally Responsible Behaviour--Bivariate descriptive analysis Environmental Worldview and Environmentally Responsible Behaviour--Metric variables--Categorical variables-- Comparing metric and categorical variables--Conclusion--Age, Environmental Worldview and Environmentally Responsible Behaviour--metric variables--Categorical variables--Gender,Environmental Worldview and Environmentally Responsible Behaviour--Explanatory analysis--Bivariate analysis--Categorical variables--Categorical and metric variables: means analysis--Metric variables-- Multivariate analysis--Categorical variables--EWVGSC and WILLACT with ERB--WILLACT, Age and Gender with ERB--Categorical and metric variables: means analysis--EWVGSC and WILLACT with ERB--WILLACT and Gender with ERB--Metric variables--Partial correlation--Multiiple regression--Conclusion--Notes.