The Second Edition of Interpreting Quantitative Data with IBM SPSS Statistics is an invaluable resource for students analyzing qualitative data with IBM SPSS Statistics for the first time. The book clearly sets out a range of statistical techniques and their common applications, explaining their logic and links to the research process. It also shows how IBM SPSS Statistics can be used as a tool to aid analysis. Key Features of the Second Edition: • New chapters on ANOVA Factor Analysis and General Multilinear Model • IBM SPSS Statistics lab sessions following each chapter which demonstrate how IBM SPSS Statistics can be used in practice • Sets of exercises and ‘real-life’ examples to aid teaching and learning • Lists of key terms and further reading to enhance students' understanding • An improved text design making the book easier to navigate
The purpose of this chapter is to examine the logic of hypothesis testing and to apply it in simple cases of testing a hypothesis for a mean or a proportion.
After studying this chapter, you should know:
- what is the logical reasoning underlying hypothesis testing;
- how to formulate the null and alternative hypotheses;
- the three forms of the alternative hypothesis;
- how to determine the acceptance and the rejection regions;
- how to reach the decision to accept or reject an alternative hypothesis;
- how to perform and interpret simple t-tests.
Hypothesis testing is, with estimation, an important mode of reasoning in inferential statistics. It is a process by which one proposition is accepted against another and which provides at the same time the probability of error in making that decision. To illustrate ...