Scholarlink

This chapter provides a comprehensive exploration of hypothesis testing. It explores the principles of falsification as advocated by Karl Popper and the application of these principles in statistical hypothesis testing through the Neyman–Pearson approach. The chapter covers the construction and testing of null (H0) and alternative (H1) hypotheses, the interpretation of Type I and Type II errors (α and β errors). It provides practical examples using statistical software such as R, SPSS, Stata, and Excel, and explains various parametric and nonparametric tests including z-tests, t-tests, ANOVA, Mann–Whitney U test, Kruskal–Wallis test, Wilcoxon signed-rank test, Wilcoxon rank-sum test, chi-square test, as well as tests for normal distribution.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Hypothesis Testing

  • 章节

  • 发表日期：

    2025年

查看全文
  • Thomas Cleff

摘要

This chapter provides a comprehensive exploration of hypothesis testing. It explores the principles of falsification as advocated by Karl Popper and the application of these principles in statistical hypothesis testing through the Neyman–Pearson approach. The chapter covers the construction and testing of null (H0) and alternative (H1) hypotheses, the interpretation of Type I and Type II errors (α and β errors). It provides practical examples using statistical software such as R, SPSS, Stata, and Excel, and explains various parametric and nonparametric tests including z-tests, t-tests, ANOVA, Mann–Whitney U test, Kruskal–Wallis test, Wilcoxon signed-rank test, Wilcoxon rank-sum test, chi-square test, as well as tests for normal distribution.