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Mar 29, 2017 11:52 AM
(1599 views)

I am doing an independent sample t-test, and I've encountered a problem with the degrees of freedom. What I'd like to do is use the floor (13 in the attached analysis), not the unrounded (13.65148), *df*, in calculating the confidence interval and *p* value. Is there a setting I can change in JMP so that it uses the floor of the *df*? Thank you.

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Mar 30, 2017 2:15 AM
(2978 views)

You have two choices. First of all, you could use the built-in function to compute your t test. Use the **t quantile( p, df )** function in a column formula or in a script. Truncating the DF is more conservative but it seems arbitrary to me. Second of all, you can simply use a different alpha. Click the red triangle next to Oneway and select a new significance level for computing the confidence intervals. Of course, you can apply a new alpha value in your decision based on the given p-value without change. This way seems better to me because you know how conservative the new t test is.

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Mar 29, 2017 12:05 PM
(1593 views)

I believe that the fractional degrees of freedom for the error arises when you use the unpooled version of the *t* test. This is correct for that case. The pooled *t* test does not adjust the DF for the error and is correct if the assumption of equal variance is valid.

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Mar 29, 2017 6:13 PM
(1578 views)

Thank you for your reply. I should clarify, though, that I am assuming unequal variance between the two populations, so I do not think the pooled variance is correct here. In order to be more conservative, I would like JMP to use the floor of the *df* in the calculations for an unpooled t-test. Is this possible?

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Mar 30, 2017 2:15 AM
(2979 views)

You have two choices. First of all, you could use the built-in function to compute your t test. Use the **t quantile( p, df )** function in a column formula or in a script. Truncating the DF is more conservative but it seems arbitrary to me. Second of all, you can simply use a different alpha. Click the red triangle next to Oneway and select a new significance level for computing the confidence intervals. Of course, you can apply a new alpha value in your decision based on the given p-value without change. This way seems better to me because you know how conservative the new t test is.

Learn it once, use it forever!

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Mar 30, 2017 10:14 AM
(1558 views)

Thank you. I've made a table that gives the *p* and confidence interval from given values. My professor for this class prefers rounding down the *df*, as it is an introductory course and we do many calculations by hand and then look up the value in a table with only integers for *df*.