I am willing to write a program for calculating the critical t values,preferably in R.

I am aware of the functions used for the same.

But, I am interested in getting aware of the mathematical procedure involved in its calculation.

Using that procedure, I want to make a program of my own, **without using any of the in built functions.**

**Contents**hide

#### Best Answer

Critical values are quantiles of the distribution. There are numerous ways to approximate quantiles (inverse cdf) of the t-distribution.

Since you have R already, one way is readily found by looking at how R does it; this is referenced in the help (`?qt`

)), under "**Source**":

For central qt, a C translation of

Hill, G. W. (1970) Algorithm 396: Student's t-quantiles. Communications of the ACM, 13(10), 619–620.

altered to take account of

Hill, G. W. (1981) Remark on Algorithm 396, ACM Transactions on Mathematical Software, 7, 250–1.

To my understanding Hill uses a modified version of a Cornish-Fisher expansion.

Other approximations are in Abramowitz and Stegun, and if I recall correctly, the tables by Pearson and Hartley as well as a number of more recent ones (both those references are even older than Hill).

If you already have an inverse beta cdf (via inverse incomplete beta function, which is available in some libraries), you can do that way — the relationship between the t cdf and the regularized incomplete beta function is given at the Wikipedia page for the t-distribution.

### Similar Posts:

- Solved – How to manually calculate values to make an F-distribution Table
- Solved – difference between qt and qnorm
- Solved – difference between qt and qnorm
- Solved – How to calculate critical values for Dunnett procedure given alpha, df1 and df2
- Solved – Why is it more useful to use inverse normal for qq plot