Statistics for Social Sciences : How to Handle and Analyse Data in Social Sciences
Who else wants to produce top quality work in social sciences? To do so you need to understand how to use statistics within social science and that is where this book can help. This book takes you to the heart of the concepts and shows you how to use these ideas in your own work. In the book the author, an experienced and sympathetic teacher with years of experience in preparing students for examinations in this field, explains clearly how to use all of the techniques to analyse your own data. This book includes explanations on: Probability and Populations; Data management & Initial data exploration; Developing & testing a hypothesis; Exploring relationships/variables 1 and 2; Scales and indices; Questionnaire survey design; Secondary data resources; and, Data analysis exercises.
- Paperback | 160 pages
- 135 x 215 x 6mm | 217.72g
- 30 Dec 2008
- Glmp Ltd
- Abergele, United Kingdom
- 2nd Revised edition
About Ian Hosker
Ian Hosker MSc gained his Masters Degree at Plymouth University. A former Lecturer in Applied Science, he is presently an industrial consultant to many major companies, on data handling. Ian Hosker lives with his family in Devon where he enjoys long country walks with his wife and partner.
Table of contents
1 Probability- The Underlying principles-probably or probability?-the likelihood of an event-the probability of multiple events-the addition rule-the multiplication rule-the probability of failure-Sources of error2 Populations and Sampling-The nature of population-Sampling a population3 Managing your data-What is a number?-Using computers to manage data-Cleaning up your database-Cells, records and variables4 Research, Questions, Concepts and Operationalism- The hypothesis-Operationalising a concept-Selecting measurable indicators-Refining your research question5 Indices and scales- Indices-scales-the semantic differential- rating and ranking6 Questionnaire design-Reliability and validity-structuring the questions-structuring the questionnaire-pitfalls in questionnaire design-the covering letter-piloting the questionnaire7 Summarising your data: frequency tables and charts-univariate analysis-frequency tables-displaying data with charts and tables8 Summarising your data: Central tendency and dispersion-Number type-measures of central tendency-standard error of measurement(se)-Using SPSS and Excel9 Hypothesis Testing-hypothesis testing- casual and associative relationships-the null hypothesis v the research hypothesis-tests of statistical significance-parametric tests- non-parametric tests10 Exploring bivariate analysis and Multi variate analysis-Bivariate analysis-Bivariate or contingency tables-creating the variable categories-the strength of a relationship - correlation-linear regression-multivariate analysis-partial correlation-multiple regression-using control variables in bivariate tables4 Research questions