Final answer:
The Unpaired T-test compares two independent means, while the Paired T-test compares means from two matched samples and uses Student's t-distribution. ANOVA tests if several population means are equal, requiring normal distribution and equal variances, using the F distribution. The Chi-square test assesses if two datasets come from the same distribution.
Step-by-step explanation:
Biostatistics often involves hypothesis testing to determine whether certain conditions or observations are due to true effects or random chance. Among the tests used are the Unpaired T-test and Paired T-test, which involve continuous data, the ANOVA for comparing means across multiple groups, and the Chi-square test, which is used for ordinal/nominal data.
The Unpaired T-test is a test to compare the means of two independent groups whereas, the Paired T-test is used to compare means from two paired or matched samples. Specifically, the Paired T-test analyzes the differences by subtracting one measurement from the other and utilizes the Student's t-distribution. The ANOVA, or Analysis of Variance, extends comparisons beyond two groups to determine if several population means are equal, requiring populations to be normally distributed with equal variances. The ANOVA utilizes the F distribution for hypothesis testing. Finally, the Chi-square test assesses independence within a contingency table and verifies if two datasets are derived from the same distribution using the chi-square distribution.