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

About the Author

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.