Syntax
T.DIST(x, deg_freedom, cumulative)
| Parameter | Description |
|---|---|
| x | Parameter of the T.DIST function. |
| deg_freedom | Parameter of the T.DIST function. |
| cumulative | Parameter of the T.DIST function. |
Examples
Left-tail probability at t=2 with 15 df
Formula
=T.DIST(2, 15, TRUE)
Returns ~0.9681. About 96.8% of the t-distribution with 15 degrees of freedom falls at or below t=2.
PDF value for plotting
Formula
=T.DIST(0, 10, FALSE)
Returns ~0.3891. The height of the t-distribution curve at t=0 with 10 degrees of freedom, useful for charting the distribution.
P-value for one-sided test
Formula
=1-T.DIST(2.5, 20, TRUE)
Returns ~0.0106. The right-tail p-value for a test statistic of 2.5 with 20 degrees of freedom is about 1.1%, suggesting significance at the 5% level.
Common Errors
#NUM!
Degrees of freedom must be at least 1. If deg_freedom < 1, this error is returned.
#VALUE!
Occurs when arguments are non-numeric.
Tips
Left-tail CDF
T.DIST with cumulative=TRUE returns the left-tail probability. For right-tail, use T.DIST.RT or calculate 1 - T.DIST(x, df, TRUE).
Converges to normal
As degrees of freedom increase (above ~30), the t-distribution closely approximates the standard normal. For large samples, z-tests and t-tests give nearly identical results.
Degrees of freedom = n - 1
For a single-sample t-test, degrees of freedom is the sample size minus 1. For a two-sample test, the calculation depends on the test type.
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