Doing Quantitative Research in the Social Sciences : An Integrated Approach to Research Design, Measurement and Statistics

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Summary: Doing Quantitative Research in the Social Sciences
Review: There should be a table of contents of this book on theweb. If I had known it, I would not have ordered this book.The title and the contents of this book are really mismatching. I thought the book was about more practical applications of quantitative research methods to the social sciences. In reality, however, the book is about elementary-level statistics assisted by a simple computer software, accompanied by an introduction to social research methodology.

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Summary: Book Contents and author's description
Review: This book is aimed at students in the social sciences, education and related subjects who have only a basic background in statistics and quantitative research design. The emphasis is on the design and execution of research projects, and includes issues of planning and sampling, measurement, choice of statistical model, and interpretation of results. Frequently, the topics research design, measurement and statistics tend to be covered in three separate texts and any links are left to the struggling student or novice researcher, who too often finds it difficult to integrate these. The aim of this book is to encourage researchers to consider all the assumptions and their interactions when making decisions during the planning of research. They need to take into account the interrelationships between 'technologies' when designing the structure of the study, creating measuring instruments, collecting data, selecting statistical tools, and interpreting the results. Therefore, the statistical tests are not just after-the-fact, but are used as part of the planning process to help make such decisions as sample size and desired reliability of instruments.

The titles of the chapters are: Part I: Introduction to Research Design 1The Nature of Enquiry 2Beginning the Process 3Initial Sources of Invalidity and Confounding 4Basic Designs 5Identifying Populations and Samples 6Additional Sources of Confounding by the Measurement Process and Interactions 7Refining the Designs

Part II: Measurement Design 8Principles of Measurement and Collecting Factual Data 9Measuring Attitudes, Opinions and Views 10Measuring Achievement 11Evaluating Data Quality: Determining Instrument Reliability and Validity

Part III: Turning Data into Information Using Statistics 12Descriptive Statistics Using a Spreadsheet 13Probability and Statistical Significance 14Power of Statistical Tests Part IV: Ex Post Facto, Experimental, and Quasi-experimental Designs: Parametric Tests 15Comparing Two Groups: t-test 16One-way Analysis of Variance: ANOVA 17Factorial Designs 18Randomised Block Designs and Analysis of Covariance

Part V: Non-Parametric Tests: Nominal and Ordinal Variables 19Nonparametric Tests: One- and Two-Sample 20Nonparametric Tests: Multiple- and Related-Samples

Part VI: Describing Non-causal Relationships 21Correlation and Association 22Regression