STC 262 Lecture Notes - Lecture 6: Sampling Distribution, Dependent And Independent Variables

• School: Miami University
• Department: Strategic Communication
• Course: STC 262
• Professor: Sasha

Document Summary

Testing for differences in categories or groups. When we have one or more nominal or ordinal variables, we test for differences among the categories of those variables. Each has its own sampling distribution that is normally distributed. Degrees of freedom is calculated for each statistic. Df refers to the number of scores in a sample that are free to vary when estimating the statistic in the population. Chi-square tests for differences between categories of two variables. Four assumptions: both variables measured at at the nominal/ordinal level, random sample. Compares the means of an interval variable on a nominal variable with two categories. The dependent variable must be measured at the interval/ratio level. The independent variable must be measured at the nominal/ordinal level with two categories. Dependent variable must be normally distributed in both groups. The variance for the dependent variable in both groups will be equal.