PSYC 60 Chapter Notes - Chapter 15: Pearson Product-Moment Correlation Coefficient, Null Hypothesis, Frequency Distribution
Document Summary
15-1 parametric and nonparametric statistical tests: parametric tests: tests that concern parameters and require assumptions about parameters. Require numerical score for each individual in sample. Require data from interval or ratio scale: nonparametric tests (distribution-free tests): alternatives to parametric tests when assumptions are violated or situations don"t conform to requirements of parametric tests. Data on nominal or ordinal scales; don"t produce numerical values that can be used to calculate means and variances: situations when better to use nonparametric tests. Original scores may violate assumptions that underlie certain statistical procedures. Original scores may have unusually high variance. An experiment produces an undetermined or infinite score. 15-2 the chi-square test for goodness of fit: test designed to answer questions about proportions in the population, uses sample data to test hypotheses about the shape or proportions of a population distribution. 15-2a the null hypothesis for the goodness of fit test: specifies the proportion/percentage of the population in each category.
