Data Construction and Data Analysis for Survey Research
Published on 19. May 2020
XX, 248 pages
978-1-137-08944-1 (ISBN)
Description
This book provides an accessible and easy-to-follow guide to survey data analysis for marketing and social science students.
Avoiding the more usual statistics-driven perspective, it provides an intuitive feel for handling survey data by emphasising that data analysis is more about understanding the research objectives and understanding what kinds of data have been collected and how. The book concludes by giving a review of strategies for coping with all the kinds of practical problems that arise in survey research.
Reader-friendly throughout, Data Construction and Data Analysis for Survey Research provides numerous worked examples, end-of-chapter questions and points for further discussion to help reinforce concepts learnt. A companion website will feature teaching support material for lecturers as well as worked examples in SPSS.
Avoiding the more usual statistics-driven perspective, it provides an intuitive feel for handling survey data by emphasising that data analysis is more about understanding the research objectives and understanding what kinds of data have been collected and how. The book concludes by giving a review of strategies for coping with all the kinds of practical problems that arise in survey research.
Reader-friendly throughout, Data Construction and Data Analysis for Survey Research provides numerous worked examples, end-of-chapter questions and points for further discussion to help reinforce concepts learnt. A companion website will feature teaching support material for lecturers as well as worked examples in SPSS.
More details
Other editions
Additional editions
Book
08/2001
Red Globe Press
€99.60
Shipment within 15-20 days
Person
RAY KENT is Senior Lecturer in Marketing at University of Stirling. He has previously published textbooks on marketing and social research.
Content
The Nature of Survey Data.- The Measurement of Variables.- Error in Measurement.- The Data Matrix.- Statistical Procedures for Analysing the Data Matrix.- Tables and Charts for Categorical Variables.- Tables and Charts for Metric Variables.- Data Reduction for Categorical Variables.- Data Reduction for Metric Variables.- Statistical Inference for Categorical Variables.- Statistical Inference for Metric Variables.- Testing Hypotheses and Explaining Relationships.- Strategies for Analysing a Data Matrix.- Analysing Qualitative Data.
