Cross Cultural Tourism Behaviour Homepage Routledge跨文化旅游行为 首页 劳特利奇.doc

Cross-Cultural Tourism Behaviour concepts and analysis Yvette Reisinger, PhD and Lindsay W. Turner, PhD CONTENTS Hypothesis testing for cross-cultural comparison 1 Introduction to parametric and non-parametric hypothesis testing 2 The hypothesis test 3 Parametric hypothesis test 3.1 When to use z and t-tests 3.2 One- and two-tailed tests 3.3 One-sample means test example 3.4 Type I and Type II errors 3.5 Two-sample means test 3.6 Unpaired test 3.7 Paired sample test 3.8 Hypothesis interpretation 4 Introduction to non-parametric hypothesis testing 4.1 One-sample non-parametric test 4.2 Paired two-sample non-parametric test 4.3 Unpaired two-sample non-parametric test 4.4 Multiple paired sample test 4.5 Multiple unpaired sample test 5 Cross-cultural behaviour: example analysis Summary 160 Discussion points and questions References and further reading Additional references Glossary Hypothesis testing for cross-cultural comparison OBJECTIVES: After completing this text the reader should be able to: understand the difference between parametric and non-parametric hypotheses tests conduct one- and two-sample parametric hypotheses tests conduct a range of non-parametric hypotheses tests understand the application of hypothesis testing to cultural tourism analysis 1. Introduction to parametric and non-parametric hypothesis testing Statistical inference procedures enable researchers to determine, in terms of probability, whether the observed differences between sample data could easily occur by chance or not. Whenever random data is collected – usually in tourism this is by some type of survey – there are likely to be some differences between the survey data and the general population at large or between different samples. For example, a comparison of the average age (the sample statistic) between Japanese touri