1. Dependent Means T Test T = M – 0 /Sm Like Z test only slightly more strict (.05 alpha requires >1.65) Why?

2. T distribution table

3. Calculating T

4. T test for independent means T = (M1 – M2) / Sdifference Df total = df1 + df2 S 2 difference is S 2 m1 + S 2 m2 S 2 m1 is S 2 Pooled/N1 S 2 Pooled is df1/df (S 2 1 ) + df2/df (S 2 2 )

7. One way ANOVA Assumptions – Independence – Normality – Equal variance of groups Calculations – Between groups variability: S 2 B = Σ n i * (M i – GM) 2 /df B [df B = NGroups-1] Larger value means bigger gap between groups so increases reason to reject null hypothesis. Numerator of F – Within groups variability: S 2 W = Σ (X iG –M G ) 2 / df W [df W is sum of group df’s] Larger value means more overlap so decreases reason to reject NH so is the denominator of F – F = S 2 B / S 2 W look up alpha criterion using df B AND df W

9. One way ANOVA