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# t2int()

Usage:
 ```t2int(x1,x2,Coverage [, pooled:F]), x1 and x2 REAL vectors or matrices with ncols(x1) = ncols(x2), 0 < Coverage < 1 ```

Keywords: probabilities, descriptive statistics, confidence intervals
```t2int(x1,x2,Coverage), where x1 and x2 are REAL vectors, computes a (two
sided) t confidence interval for mu1 - mu2 with confidence coefficient
Coverage, where mu1 is the population mean of the data in x1 and mu2 is
the population mean of the data in x2.  A pooled estimate of the
standard error of the difference is used.  This assumes equal variances.

Coverage must be between zero and one.  The value is a vector of length
2 giving the lower and upper endpoints of the interval.

t2int(x1,x2,Coverage,pooled:F) computes a confidence interval for
mu1-mu2 based on the unpooled estimate sqrt(s1^2/n1+s2^2/n2) of the
standard error and Satterthwaite's approximate degrees of freedom.  It
does not assume equal variances.

If there are any missing values, they are omitted from the computation
and an informative message is printed

When x1 and x2 are REAL matrices with ncols(x1) = ncols(x2) = M,
t2int(x1,x2,Coverage [,pooled:T]) computes confidence intervals for each
column.  The result is a 2 by M matrix with the lower and upper limits
in rows 1 and 2, respectively.

See also tint(), tval(), and t2val().
```

Gary Oehlert 2003-01-15