Question

The situation…
• A 12-month email study looked at the click-through responses triggered by two versions of email, Version A and Version B.
• In all 24 distributions (12 for Version A; 12, Version B) emails were drawn randomly.
• People receiving A or B versions were unrelated (randomly selected every time for both version of the email).
• The researchers had no idea which version would trigger more clicks.
• Alpha was set at p <.05.
Month	Email Response-Rate Study
	Group A	Group B
January	36	36
February	35	25
March	24	29
April	23	37
May	29	37
June	12	23
July	18	27
August	12	21
September	14	24
October	24	33
November	25	32
December	33	40
Mean	23.75	30.33
SD	8.51	6.37
Variance	72.39	40.61
t test	0.044
Effect Size	-0.77
Using this scenario and the data above, respond to all of the following items:
1.
What type of t test would you use? Why?

-0.77

Answer 1

Here we need to use two sample independent t-test. Because the sample is taken randomly from both the groups.

next we need to decide "is it pooled t-test or unpooled t-test?"

For this we need to test equality of two variances.

Null hypothesis:

H₀ : both the variances are equal

Alternative hypothesis:

H_a : They are different.

Let's use minitab:

Step 1) Click on Stat >>>Basic Statistics >>>2-Variances ...

Fill the necessary information and then click on Option again fill the necessary information.

Look the following image:

Then click on OK again Click on OK , so we get the following output:

From the above output, the p-value is as follow:

p-value = 0.352

Since p-value > 0.05 we fail to reject the equality assumption of two populations.

So that the pooled procedure more appropriate in this situation.

that is we need to used pooled t-test.