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F-Test (for difference in variance)
use for difference in variances/dispersion Ho= all same Ha= at least 2 different
F-Test do not reject null
p>alpha perform an independent sample t-test for difference in means (equal)
F-Test reject null
p<alpha perform an independent sample t-test for difference in means (unequal)
z-test for population proportion
testing for how one population compares to a constant
chi square test
comparing a population variance to a constant value
z test for difference in proportions
interested in two different populations, want difference
independent samples t-test for difference in mean - unequal variances
when you reject the null for an F test
paired sample t-test for difference in means
unknown standard deviation, testing the average difference
independent samples t test for difference in means - equal variances
do not reject null for F test (samples not different), comparing means of 2 populations without knowing variance
F-test difference in means
comparing means of more than 2 populations
z test for difference in means
comparing two population means and know variance
t test for the mean
testing mean of one population, standard deviation unknown
z test for mean
testing mean of one population, standard deviation known
F test
ratio of two variances Ho --> ratio=1

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