PSYC 2002 Chapter Notes - Chapter 15: Null Hypothesis, Frequency Distribution, N100

• School: Carleton University
• Department: Psychology
• Course: PSYC 2002
• Professor: Donna Mailloux

Document Summary

Statistics chapter 15: the chi-square test of independence. Often, researchers are confronted with experimental situations that do not conform to the requirements of parametric tests (requiring assumptions about parameters). There are several hypothesis-testing techniques that provide alternatives to parametric tests. For nonparametric tests, participants are usually classified into categories such a democrat and. There measurements involve measurement on nominal or ordinal scales, and do not produce numerical values that can be used to calculate means and variances. The data for nonparametric tests are simply frequencies example: the number of democrats and republicans in a sample of n=100 registered voters. The chi-square test for independence evaluates the relationship between two variables using the same chi-square formula as the test for goodness of fit. The null hypothesis states that the two variables are independent of each other. The observed frequency is the number of individuals from the sample who are classified in a particular category.