Statistical Testing
Statistical Testing covers hypothesis testing, one of the most important methodologies in statistics, and introduces basic theories as well as various tests frequently used in practice. In particular, the content in the Advanced section originated from the complaint “please write down what the null hypothesis and alternative hypothesis are, not just output the test statistic and p-value,” and it is certain that it will be helpful to many statistics students.
- In particular, the posts in the Beginner section carefully explain the derivation process of hypothesis tests that must be accepted without mathematical proof when you are an undergraduate freshman. Even if you advance to higher grades, it is difficult to understand the proof at the undergraduate level, but if you are at the level of a graduate student, it is recommended to review them as you go through.
Beginner
- Simple Definition of Hypothesis Testing
- Rejection Region and Significance Level
- P-value or Significance Probability
Inference on Population Mean
- Large Sample Hypothesis Test for Population Mean
- Small Sample Hypothesis Test for Population Mean
- Large Sample Hypothesis Test for Difference of Two Population Means
- Small Sample Hypothesis Test for Difference of Two Population Means
Chi-squared Test
- Pearson Chi-squared Test Statistic $\mathcal{X}^{2}$
- Population Variance Estimation for Groups Following Normal Distribution
ANOVA
- Experimental Design CRD, RBD
- Analysis of Variance or ANOVA?
- ANOVA Table
- F-test in ANOVA
- One-way ANOVA
- Two-way ANOVA
Nonparametric Statistics
- What is Nonparametric Statistics?
- Rank in Statistics
- Mann-Whitney $U$ Test
- Wilcoxon Signed-rank Test
- Kruskal-Wallis $H$ Test
- Friedman $F_{r}$ Test
- Spearman Rank Correlation Coefficient $r$
Advanced
Distribution Testing
Regression Analysis
- t-test for Regression Coefficients
- F-test for Regression Coefficients
- Hosmer-Lemeshow Goodness-of-fit Test
Time Series Analysis
Main References
- Mendenhall. (2012). Introduction to Probability and Statistics (13th Edition)
- Department of Statistics, Kyungpook National University. (2008). Statistics Using Excel
All posts
- How to Set the Null Hypothesis and Alternative Hypothesis
- Type I and Type II Errors Difference
- Rejection Region and Significance Level
- Easy Definition of P-Value or Significance Probability
- Regression Coefficient's t-test
- F-test for Regression Coefficients
- Hosmer-Lemeshow Goodness of Fit Test
- Shapiro-Wilk Test
- Jarque–Bera test Test
- Dickey-Fuller Test
- Box-Cox Transformation
- Durbin-Watson Test
- Run-Test
- McLeod-Li Test
- Simplified Definition of Hypothesis Testing
- Hypothesis Testing for Population Mean
- Large Sample Hypothesis Testing for the Difference Between Two Population Means
- Hypothesis Testing for the Population Mean with a Small Sample
- Small-Sample Hypothesis Testing for the Difference Between Two Population Means
- Pearson Chi-Square test statistic
- Polynomial Experiments and Contingency Tables
- Fitness Test of a group
- Test of Independence
- Test of Homogeneity of Population
- Estimation of Population Variance for Normally Distributed Groups
- Experimental Design in Statistics
- What is Analysis of Variance or ANOVA in Statistics?
- ANOVA Table
- F-test in Analysis of Variance
- One-way Analysis of Variance
- Two-way ANOVA
- What is Non-parametric Statistics?
- Rank in Statistics
- Mann-Whitney U Test
- Sign Test in Statistics
- Wilcoxon Signed-Rank Test
- The Mean and Variance of Ranks in Statistics
- Kruskal-Wallis H Test
- Friedman Fr Test
- Spearman Rank Correlation Coefficient r
- What is p-hacking?
