Hypothesis Testing Clarification.
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 This topic has 6 replies, 6 voices, and was last updated 13 years, 10 months ago by cait.

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May 11, 2004 at 8:49 pm #35507
Brad M.Participant@BradM. Include @BradM. in your post and this person will
be notified via email.Can someone give me a laymens explanation as to why you calculate the F Test statistic before you calculate the t Test statistic? I understand that you are looking for the variances to be statistically similar with the F Test but what happens if you find that they are not? Does this mean that the t Test cannot be calculated or will be meaningless if calculated? Also, two processes with statistically dissimilar variances but statistically similar means is significant isnt it? Wouldnt the process with less variation in it be a better process even if the means are statistically similar? Thanks for your feedback.
0May 11, 2004 at 9:34 pm #100070
Ken FeldmanParticipant@Darth Include @Darth in your post and this person will
be notified via email.The Minitab default for the 2sample t test is that the variances are unequal. There is an option to select equal variances. It is useful to do the F test first to ascertain which is more representative of the data.
0June 3, 2004 at 2:42 pm #101185The purpose of running the F test first is to determine which of the 2 Ttests to use. If the Ftest shows equal variances, then use the Ttest for equal variances. If the Ftest shows unequal variances, then use the Ttest for unequal variances. The point is to improve the precision of the Ttest by matching the proper method to the data. And yes, there can be separate indications of significance (or not) between the variances and means without one voiding the other. I find it useful to do the F test first for 2 reasons: first to select the proper Ttest, and second to test the equality of the variances which might reveal meaningful differences.
0June 4, 2004 at 9:37 am #101225
S.K.BagriMember@S.K.Bagri Include @S.K.Bagri in your post and this person will
be notified via email.Dear Mr. Brad,
ttest is applied for hypothesis test of mean when population standard deviation is unknown.
Alternatively, Ftest signifys homogenity of two variance among two population.
Hope it is clear.
S.K.Bagri.0June 6, 2004 at 2:33 am #101284
jediblackbeltParticipant@jediblackbelt Include @jediblackbelt in your post and this person will
be notified via email.I typically use the Ftest to determine if I am eligible for ANOVA. If the Ftest shows variances are equal then I use ANOVA for my results. If I fail to accept the null on Ftest then I use Ttest without equal variances.
0June 6, 2004 at 4:08 pm #101289
Ken FeldmanParticipant@Darth Include @Darth in your post and this person will
be notified via email.Oh, young Jedi, do you really use the F test before deciding on ANOVA? Or do you use Test for Equal Variances dba Bartlett and Levene’s test, which are sort of special cases of the F test? ANOVA is for more than 2 means and B&L is for more than two variances. The simple F test is usually for 2 variances as is the 2sample t. So which is it?
0November 17, 2008 at 12:25 am #177720What I don’t really understand is how to tell if the variances are equal or unequal. I don’t remember what my teacher said!! Does it have to do with the alpha level? Can someone give me an example of when it would be equal or unequal?
HELP!0 
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