Nonparametric tests are used for ______________ and _____________ data, while Parametric tests are preferable for __________________ and ________________ data.
- Nominal and Ordinal
- Interval and Ratio
Both Parametric and Nonparametric tests assume that observations are ___________________, which means that a subject’s participation in the study or performance on the DV is not affected by or related to the participation or performance of any other subject.
Independent.
____________________ tests (e.g., T-test, ANOVA) are used to evaluate hypotheses about population means, variances, and other parameters.
Parametric tests.
Two assumptions of Parametric tests are:
- That the value of interest is ____________________ in the population
- When a study includes more than one group, there is _____________________ - that is, the variances of the populations that the different groups represent are equal.
However, Parametric tests are still rather robust with regard to violation of their assumptions.
- Normally distributed
- Homoscedasticity
The most effective way to maximize the robustness of a parametric test is to have an _________________ of subjects in each group; robustness is also increased by having a ______________ sample size and setting alpha at a __________ level.
- Equal number
- Large
- Lower
_____________________ are used to analyze data collected on variables that have been measured on a nominal or ordinal scale, and are referred to as “distribution-free” tests. They are used to evaluate hypotheses about the shape of a distribution rather than the distribution’s mean, variance, or other parameter. They are less powerful than Parametric tests.
Nonparametric.
The magnitude of the critical value (which divides the sampling distribution into rejection and retention regions) is determined by _____________ and the ___________________.
- Alpha
- Degrees of Freedom
____________________ are the number of values or categories in a distribution that are “free to vary” given that certain values or categories are known or fixed.
Degrees of Freedom.
The method used to calculate the DF depends on the statistical test; for the t-test for a single sample, the sampling distribution is based on the sample size, and the degrees of freedom are derived from the total number of subjects (__ - __). When using a single-sample Chi-square test, the sampling distribution is based on the number of categories (levels) of the variable, and the DF are derived from the total number of categories (__ - __).
- (N - 1)
- (C - 1)
