10.1 Two Population Means with Unknown Standard Deviations
Standard error SE = √(s1)2n1+(s2)2n2
Test statistic (t-score) t = (ˉx1−ˉx2)−(μ1−μ2)√(s1)2n1+(s2)2n2
Degrees of freedom
where
s1 and s2 are the sample standard deviations, and n1 and n2 are the sample sizes.
ˉx1 and ˉx2 are the sample means.
Cohen’s d is the measure of effect size
d=ˉx1−ˉx2spooled
10.2 Two Population Means with Known Standard Deviations
Normal distribution
Test statistic (z-score)
where
10.3 Comparing Two Independent Population Proportions
Pooled proportion pc = xF + xMnF + nM
Distribution for the differences
where the null hypothesis is H0: pA = pB or H0: pA – pB = 0.
Test statistic (z-score): z=(p′A−p′B)√pc(1−pc)(1nA+1nB)
where the null hypothesis is H0: pA = pB or H0: pA − pB = 0
and where
p′A and p′B are the sample proportions, pA and pB are the population proportions,
Pc is the pooled proportion, and nA and nB are the sample sizes.
10.4 Matched or Paired Samples (Optional)
Test statistic (t-score): t = ˉxd−μd(sd√n)
where
ˉxd is the mean of the sample differences, μd is the mean of the population differences, sd is the sample standard deviation of the differences, and n is the sample size.