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


© 1999 | 768 pages | SAGE Publications Ltd
At lastùa lucid, comprehensive, and integrated approach to using quantitative methods in the social sciences. Author Thomas R. Black's method focuses on designing and executing research so that issues such as planning, sampling, designing measurement instruments, choosing statistical tests, and interpreting results are integrated into the research process. Black's how-to approach guides the student and researcher through the minefield of issues they are confronted with when doing research, as well as setting it apart from other books that focus on either research design and measurement issues or statistical methods. Written in a lively, accessible style, the student is introduced to research design issues along with statistical procedures necessary for data analysis that develops the student's analytical skills and decision-making powers. An ideal textbook for students across the social sciences, Doing Quantitative Research in the Social Sciences includes a wide range of examples and activities providing the student with a solid foundation in research design, measurement, and statistics.
 
PART ONE: INTRODUCTION TO RESEARCH DESIGN
 
The Nature of Enquiry
 
Beginning the Design Process
 
Initial Sources of Invalidity and Confounding
 
Basic Designs
 
Identifying Populations and Samples
 
Additional Sources of Confounding by the Measurement Process and Interactions
 
Refining the Designs
 
PART TWO: MEASUREMENT DESIGN
 
Principles of Measurement and Collecting Factual Data
 
Measuring Attitudes, Opinions and Views
 
Measuring Achievement
 
Evaluating Data Quality
Determining Instrument Reliability and Validity  
 
PART THREE: TURNING DATA INTO INFORMATION USING STATISTICS
 
Descriptive Statistics Using a Spreadsheet
 
Probability and Statistical Significance
 
Power, Errors and Choosing a
 
PART FOUR: EX POST FACTO, EXPERIMENTAL AND QUASI-EXPERIMENTAL DESIGNS: PARAMETRIC TESTS
 
Comparing Two Groups
t-Test  
 
One-Way Analysis of Variance
 
Factorial Designs
 
Randomized Block Designs and Analysis of Covariance
 
PART FIVE: NONPARAMETRIC TESTS: NOMINAL AND ORDINAL VARIABLES
 
Nonparametric Tests
One and Two Samples  
 
Nonparametric Tests
Multiple and Related Samples  
 
PART SIX: DESCRIBING NON-CAUSAL RELATIONSHIPS
 
Correlation and Association
 
Regression

`There is much that is excellent about this book. If all educational researchers had studied it thoroughly, especially the sections on research design, representative samples and confounding variables, then there might be less publication of sweeping statements based on insufficient evidence' - British Educational Research Journal


Not an easy read for novices

Dr Bahadir Namdar
Primary Education/ Science Education Program, Recep Tayyip Erdogan University
February 22, 2017

I personally found this book a very interesting read, but unfortunately this is not pitched at an appropriate level for our students. This is not a comment on the book, rather the structure of our course(s) and the outputs that our students are expected to produce. Many thanks.

Dr Jim Clack
Department of Primary Education, Bedfordshire University
September 29, 2014

Doing quantitative research in the social sciences an integrated approach to research design, measurement and statistics contains 22 chapters which are divided into six main parts.
Part one introduction to research design consists of seven chapters which introduce the reader to the nature of data in terms of its multiple sources and discusses the differences between empirical and non-empirical approaches to gathering data, as well as the advantage of using a scientific approach to conducting research with respect to using rigorous and methodical processes and techniques. Also, covered in part one are the issues researchers face when planning and designing research with regards to answering research questions and providing evidence of the validity of hypotheses being tested, in addition to working with and measuring variables. This section concludes with what the researcher should consider when identifying population(s) from which to sample from and part one presents a summary of the techniques which can be employed when selecting a sampling strategy, as well as key issues to consider associated with each sample strategy.
Part two measurement design consists of four chapters which focus mainly on attitude surveys measuring attitudes, opinions and views in relation to what the results from these types of instruments indicate and reveal about a given area or phenomena. Also covered in this section is the importance of construct validity with respect to enhancing the reliability of research designed instruments for gathering and measuring data, in addition to, checking the reliability and validity of instruments.
Part three turning data into information using statistics consists of three chapters which discuss the advantages of using a spreadsheet to generate frequency tables, graphs and charts, as well as how to prepare data for comparing different groups of data. The theory discussed within this section relate to probability and statistical significance with respect to the types of data which can be analysed and the effect the distribution of the data can have on the results in relation to the degree which statistical inference can be inferred. The effect that power and errors can have on data with regards to setting up significance levels and testing hypotheses are also covered in this section.
Part four ex post facto, experimental and quasi-experimental designs: parametric tests consists of four chapters and discuss the differences between experimental and quasi-experimental research designs and the types of parametric tests which can be applied when analysing and interpreting data generated from making comparisons between groups when comparing means differences.
Part five nonparametric tests: nominal and ordinal variables consists of two chapters which present an alternative to using parametric tests and discusses when to use nonparametric tests and the types of tests that can be used as a nonparametric equivalent to parametric tests for comparing medians as apposed to means differences.
Part six describing non-causal relationships consists of two chapters which cover correlation and the differences between experimental and nonexperimental research and when correlation should be used, as well as the benefits of using scatter diagrams to aid in the interpretation of correlations by representing the results graphically to determine the strength of the relationship between two variables. Regression and linear regression equations are discussed in relation to mathematical theory, a well as using two dimensional and three dimensional scatter diagrams to display frequencies and standard deviations.
Appendix provides a useful introduction to using spreadsheets for presenting data analysed diagrammatically and how to amend or update information to a completed spreadsheet of data. The appendix also presents a helpful set of statistical tables showing: (1) areas under the normal distribution; (2) critical values for significance for a one-tailed test; (3) critical values for the F-distribution; (4) critical values for F-distribution as well as other useful tables. A glossary of mathematical symbols, equations and excel functions along with a definition and description of their function are provided, as well as a bibliography of helpful references. Helpful check lists are provided within chapters for the reader to check their knowledge and understanding of the information being presented in chapters.
This text covers the theory behind conducting quantitative research in the social sciences. The main focus of this book is on the theory underpinning research design and analysis using statistical techniques to test data gathered from survey questionnaires. The reading level of this text is accessible for undergraduate, postgraduate and doctorial students, as well as researchers working with quantitative data on research projects. This book is recommended as essential reading and reference material for anyone using a quantitative approach to research within the social science.

Mr Gary McKenna
School of Computing, University of the West of Scotland
March 27, 2013

A well written text-book that gives learners and teachers of quantitative research an in-depth understanding of the quantitative paradigm.

Mr Moses Murandu
School of Health & Wellbeing, Wolverhampton University
January 24, 2013

Provides a good overview of all statistical methods

Dr Karyn Morrissey
Department of Geography, Liverpool University
November 10, 2012

This book has met my expectations, additionaly I would be happy if it has SPSS applications, but excel applications are also fine. Thanks for sending it. I'll benefit it for my course.

Mr Erdem Akkan
Vocational School of Social Sciences, Mersin University
September 20, 2011

Budget cuts have forced us to not adopt a BSN program at this time.

Mrs Casey SCUDMORE
Allied Health Division, Antelope Valley College
September 10, 2011

this text is recommended for student much further in their masters degree study. it is very detailed and includes some intense statistical tests. I have made my students aware of it to consult as they progress through the masters level programme

Dr Brian Nyatanga
Nursing , Worcester University
December 8, 2010

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