Review t-tests Single-sample t-test (df = N – 1) Independent samples t-test (df = (n1 – 1)+(n2 – 1) ) Related or paired-samples t-test (df = N – 1)

ANOVA formulas One-way ANOVA dftotal = N – 1 dfbetween = k – 1 dfwithin = (n – 1) or N – k Two-way ANOVA dftotal = N – 1 dfbetween = k – 1 (or # cells -1) dfwithin = N – k (or  (n-1) ) dfA = k – 1 (# rows – 1 for factor A) dfB = k – 1 (# columns – 1 for factor B) dfAxB = dfbetween – dfA - dfB Repeated-measures ANOVA dftotal = N – 1 dfbetween = k – 1 dfwithin = N – k dfbetween subjects = n – 1 dferror = dfwithin – dfbetween subjects One-way ANOVA Repeated-measures ANOVA

Effect size analyses z-test One-sample t-test Paired samples t-test CI = M +/- z*(σM) One-sample t-test CI = M +/- t*(sM) Independent t-test CI = M1 – M2 +/- t*(sM1-M2) Cohen’s d Small >.2 Medium >.5 Large > .8 Variance accounted for (r2) Small >.01 Medium >.09 Large > .25 Paired samples t-test CI = MD ± t*(sMD) Cohen’s d ANOVA: effect size = eta2

Other formulas Goodness of fit chi-square Frequency table of data Observed frequencies (fo) Compare to null hypothesis Expected frequencies (fe) Expected frequency fe = pn Chi-square equation df = C – 1, where C = # of categories   Preference for note-taking method: frequency counts Design A: 23, Design B: 12, Design C: 25 --- n = 60