FIGURE 5.3
The 95% confidence interval for
̂
under the hypothesis that
= 0.3.
FIGURE 5.4
The 95% confidence interval for t(8 df).
which clearly lies in the critical region of Figure 5.4. The conclusion remains the same;
namely, we reject
.
Notice that if the estimated
(=
̂
) is equal to the hypothesized
, the
t
value in
(4.7.4) will be zero. However, as the estimated
value departs from the hypothesized
value, It I (that is, the absolute
t
value;
note: t
can be positive as well as negative) will be
increasingly large.
Therefore, a "large" It value will be evidence against the null
hypothesis.
Of course, we can always use the
t
table to determine whether a particular
t
value is large or small; the answer, as we know, depends on the degrees of freedom as
well as on the probability of Type I error that we are willing to accept. If you take a look
at the
t statistical
table
you will observe that for any given value of df the probability of
obtaining an increasingly large
| |
value becomes progressively smaller. Thus, for 20 df
the probability of obtaining a
| |
value of 1.725 or greater is 0.10 or 10 percent, but for
𝑡
𝑡
g
%
g
%
𝑓 𝑡
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