S W 318 Lecture Notes - Lecture 9: Statistical Inference, Null Hypothesis, Analysis Of Variance
Document Summary
An inferential statistics technique designed to test for significant relationship between two variables in two or more samples: the logic is the same as in t-tests, just extended to independent variables with two or more samples. Examines the differences between samples and within a single sample. One-way anova: an analysis of variance procedure using one dependent and one independent variable. Assumptions: independent random samples are used, the dependent variable is measured at the interval-ration level, some researchers apply anova to ordinal level measurements, the population is normally distributed, the population variances are equal. Stating the research and null hypothesis: h1: at least one mean is different from the others, h0: all means are the equal. F = difference between groups over differences within groups. Between-group sum of squares: the difference between groups. Mean square within: an estimate of the within-group variance obtained by dividing the within-group sum of squares by its degrees of freedom.
