Introduction to Statistics (MAT/SST 115.03 2008S)
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Particularly since the t-distribution table
is complicated to use, it is helpful to be able to have R do the
computation for us. R provides a procedure, qt
,
that behaves much like that table. However, qt
,
given an area, computes a t-value with that area
to the left (rather than to the right, as shown
in the table).
For a 95% confidence interval, we call qt
with
.975. (Why .975? Because there's 0.025 to the right, and therefore
0.975 to the left.) More generally, we can average the confidence
level and 1. Of course, qt
expects a second
parameter, which represents the degrees of freedom. Most generally,
we write
qt(confidence_level
+1)/2,df
)
For example, to compute t^{*} for a 95% confidence interval with a sample size of 30, we would write
qt(.975, 29)
Similarly, to compute t^{*} for a 90% confidence interval with a sample size of 100, we would write
qt(.95, 99)
Primary: [Front Door] [Syllabus] [Current Outline] [R] - [Academic Honesty] [Instructions]
Groupings: [Applets] [Assignments] [Data] [Examples] [Handouts] [Labs] [Outlines] [Projects] [Readings] [Solutions]
External Links: [R Front Door] [SamR's Front Door]
Copyright (c) 2007-8 Samuel A. Rebelsky.
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