MATH 10051 Lecture Notes - Lecture 2: Type I And Type Ii Errors, Reinforcement, Statistical Power

• School: Kent State University
• Department: Mathematics
• Course: MATH 10051
• Professor: Mary Theresa Sharp

Document Summary

Used when assumptions for parametric tests are not met. Dependent variable is a scale variable interval or ratio. If the dependent variable is ordinal or nominal, it is a non-parametric test. If there is no randomization, it is a non-parametric test. If the shape is not normal, it is a non-parametric test. Used when either the dependent or independent variable is ordinal. Cannot easily use confidence intervals or effect sizes. These variables, also called "attribute variables" or "categorical variables," classify observations into a small number of categories. A good rule of thumb is that an individual observation of a nominal variable is usually a word, not a number. Examples of nominal variables include sex (the possible values are male or female), genotype (values are aa, aa, or aa), or ankle condition (values are normal, sprained, torn ligament, or broken) Nonparametric test when we have one nominal variable. Measurement v. nominal: imagine recording each observation in a lab notebook.