Question

Why do we run post hocs when calculating an ANOVA that is significant, but not for a T-test that is significant (be sure to discuss both parts of the question to get full points)?

Answer #1

To answer this question, first we have to understand the difference between t test and ANOVA

we use t test to find the difference between two means only, whereas we use ANOVA to test difference between three or more means, but not for two means.

In case of t test, we have only two means to test for difference. This means that if there is significant difference, then we can directly conclude that there is a significant difference between the given two means

In case of ANOVA, we can’t directly say that there is a significant difference between means because we have 3 or more means. So, ANOVA just tells us that there is a significant difference between at least one pair of means. That’s why we need post hocs to find out where the difference actually exists

1. When do we decide to run an ANOVA (F test) rather than a t
test?

What is the logic behind the ANOVA analysis? When and why should
we use it instead of the T-tests that seem to be much easier to
do?
(Question is related to lean six sigma)

Q1. Why would you perform a one-way ANOVA over
a t-test? Is the answer, when the population means of only two
groups is to be compared, a t-test is used, but
when means of more than two groups are to be compared,
ANOVA is preferred (Y/N)
Q2. A rag-tag group of bandits crash the party
to steal candy. In a frenzy, you carefully record the numbers of
different candies that group grabbed. You arrange
the data in a table, below:...

What is a post-hoc test and why is it necessary to use one after
a significant ANOVA?

12. What is the total of the ANOVA split into?
16. What is a post hoc test and why don’t you need it if your
ANOVA is not significant?
18. What happens to the curve as the degrees of freedom for the
numerator and for the denominator get larger? This information was
also discussed in previous chapters.

Week 8 Discussion
Consider the different post hoc tests discussed in the readings
and respond to the following:
Describe the general rationale behind using post hoc tests
(i.e., when they are used and why).
One of the advantages of using an ANOVA (compared to using
t-tests) is also a disadvantage—using an ANOVA makes it
necessary to use post hoc tests if there is a significant main
effect. We use a post hoc test because there is one specific
advantage in...

Part a: If the interaction in a two-way factorial ANOVA
is significant, then
A.
we need to test for all main effects.
B. we need to test for simple effects.
C.
we need to test for one of the main
effects.
D. None of above.
Part B: When testing for significant mean differences
among three groups means, doing independent t tests on all possible
pairwise comparisons will
A.not change the probability of a Type I
error.
B. increase the probability...

The ANOVA is an omnibus test, this means that we have to
examine
Question 1 options:
A. effect size to determine significance
B. very large samples to find a significant difference
C. post-hoc comparisions after completing an ANOVA
D. overall differences after completing an ANOVA

When comparing means among three independent samples, will we
obtain the same results if we run a series of independent
t-tests (for pairwise mean comparisons) as those from the
one-way ANOVA? Why or why not? Explain why you believe so.

What are we calculating when we calculate expected frequencies?
What is the reason for calculating expected frequencies the way we
do? In laymen’s term, what do expected frequencies tell us?
the
previous answer to the same question really did not answer all the
questions. like the laymen’s term for expected frequency. and the
reason for calculating it.

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