1What is a Z-Test?
A hypothesis test using the standard normal distribution to determine if a sample mean or proportion differs significantly from a known value.
2When is a Z-Test commonly used?
When the population variance is known or the sample size is large enough for the central limit theorem.
3What does a Z-Test evaluate?
Whether observed data are unlikely under the null hypothesis using the normal distribution.
4What is a T-Test?
A test used to compare means when the population standard deviation is unknown or the sample is small.
5What are the types of T-Tests?
Independent (two-sample), paired (before/after), and others.
6What does a T-Test determine?
Whether two groups differ in their averages in a statistically meaningful way.
7What is skewness?
A measure of how asymmetric a distribution is around its mean.
8What does positive skew mean?
The right tail is longer.
9What does negative skew mean?
The left tail is longer.
10What is kurtosis?
A measure of how heavy or light the tails of a distribution are.
11What does high kurtosis indicate?
More data in the tails and more outliers.
12What does low kurtosis indicate?
Lighter tails and fewer extremes.
13What is a one-tailed test?
A hypothesis test predicting a specific direction, using only one tail of the distribution.
14What is a two-tailed test?
A hypothesis test checking for differences in either direction, using both tails.
15Why does tail choice matter?
It affects interpretation of p-values and critical regions.
16What is ANOVA?
A test comparing the means of three or more groups.
17How does ANOVA work?
By separating variability into between-group and within-group variance.
18Why use ANOVA instead of multiple t-tests?
It controls Type I error more effectively.
19What follows a significant ANOVA?
Post-hoc tests to identify which groups differ.
20What is Pearson’s R?
A measure of linear relationship strength and direction between two continuous variables.
21What is the range of Pearson’s R?
-1 to +1, with 0 meaning no linear correlation.
22What is a limitation of Pearson’s R?
Correlation does not imply causation.
23What is the Kruskal–Wallis H Test?
A non-parametric alternative to one-way ANOVA for comparing three or more independent groups.
24How does the Kruskal–Wallis test compare groups?
By using ranked data rather than raw values.
25What does the Kruskal–Wallis test determine?
Whether at least one group’s distribution differs from the others.
26What is the Friedman Test?
A non-parametric alternative to repeated-measures ANOVA.
27When is the Friedman Test used?
When analyzing three or more related/matched samples without assuming normality.
28How does the Friedman Test work?
By ranking data within each subject and comparing conditions.
29What is the Sign Test?
A non-parametric test for paired data considering only the direction of change.
30What does the Sign Test ignore?
The magnitude of differences.
31When is the Sign Test useful?
When assumptions about difference sizes cannot be made or data are ordinal.
32What is the Wilcoxon Signed-Rank Test?
A non-parametric test for paired data using both rank and direction.
33Why is the Wilcoxon test more powerful than the Sign Test?
It includes magnitude information through rankings.
34When is the Wilcoxon test used?
When assumptions of the paired t-test are violated or data aren’t normally distributed.