Introduction to Statistics (MAT/SST 115.03 2008S)
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While the book does not ask you to use technology in this section, I thought it would be useful for you to learn a bit about how you can use R for working with the t-distribution.
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. The qt
function
also
expects a second parameter, which represents the degrees of freedom.
For example, part d asks us to find the value of
t^{*} for a 95% confidence
interval with a sample size of 10 (9 degrees of freedom).
In R, we would write
qt(.975, 9)
Of course, you should make sure that you know how to use the table to find t^{*} and confirm that you get the same answer in both cases.
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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