The data below represent the weight losses for people on three different exercise programs. Exercise A Exercise B Exercise C
2.5 5.8 4.3
8.8 4.9 6.2
7.3 1.1 5.8
9.8 7.8 8.1
5.1 1.2 7.9
If we want to test the claim that the three size categories have the same means, why don't we use three separate hypothesis tests for μ1 = μ2, μ2 = μ3, and μ1 = μ3?
A. The risk of type l error increases and becomes too high.
B. Actually, we do want to use three separate hypothesis tests.
C. The risk of type ll error increases and becomes too high.
D. A hypothesis test for comparing two means does not exist.

A. The risk of type l error increases and becomes too high.

Step-by-step explanation:

The overall level of significance increases as the number of t- tests ( used for comparing two, three or four means separately ) increases. This in turn increases the risk of type I error.

We might be tempted to apply the two sample t- test to all possible pairwise comparisons of means. This type of running t- test to several means comparison has the risk of increasing overall level of significance

hello from mrbilldoesmath!

answer:

the domain is the set { -2, 0, 2, 3}

discussion:

the domain is the set of x values in the ordered pairs (x,y). taking the x, or first component, of each ordered pair gives   -2, 0, 2, 3.

you,

mrb