### One-sample tests:

- t test (test
whether population
**mean**is equal to hypothesized value) - sign test (test the hypothesis that the probability of a random value from the population being above the specified value is equal to the probability of a random value being below the specified value)
- Wilcoxon signed rank test
(test whether population
**median**is equal to hypothesized value)

- t test (test
whether population
### Paired two-sample tests:

- t test (test
whether population
**mean**of paired differences is 0) - sign test (test the hypothesis that the probability of a paired difference being above 0 is equal to the probability of a paired difference being below 0)
- Wilcoxon signed rank
test (test
whether population
**median**of paired differences is 0) - McNemar's Q (test
whether population
**median**of paired differences is 0 --**dichotomous**outcome variable, counted data arranged in "contingency" table)

- t test (test
whether population
### Two-sample (unpaired) tests:

- t test (test
whether two population
**means**are equal) - Mann-Whitney rank sum test
(test whether two population
distribution functions
are identical against the alternative that they differ by
**location**)

- t test (test
whether two population
### Multi-sample one-way tests:

#### Unblocked

- One-way ANOVA
(unblocked) (test whether several treatment effects
(
**means**) are equal) - Kruskal-Wallis test
(test whether several population
distribution functions
are identical against the alternative that they differ by
**location**)

- One-way ANOVA
(unblocked) (test whether several treatment effects
(
#### Blocked

- One-way
ANOVA (blocked) (test whether several treatment effects (
**means**) are equal) - Friedman's test
(test whether several treatment effects (
**locations**) are equal) - Cochran's Q (test
whether several treatment effects (
**locations**) are equal --**dichotomous**outcome variable)

- One-way
ANOVA (blocked) (test whether several treatment effects (

### Multi-factor ANOVA

- Multi-factor
ANOVA (test simultaneously the significance of the effect of multiple
factors on treatment
**means**)

- Multi-factor
ANOVA (test simultaneously the significance of the effect of multiple
factors on treatment

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