Chapter 13 and 14

Error  Type 1: False positive. The effect was not really present, but our statistics lead us to believe that it is.  Type 2: False negative. The effect really is present, but our statistics are not able to detect it.

Sample size effects  In small sample sizes, it is more difficult to find true effects (type II error is greater)  In large sample sizes, it is easier to find true effects, but also easier to find false effects (type I error is greater, type II error is smaller)

Test statistics  Most common are F, t, chi-square  Looking for a significance level p of less than.05.

ANOVA: Analysis of Variance  Do the group means differ significantly?  ONE dependent variable  MANOVA: multiple analysis of variance – two or more dependent variables