On Thu, 8 Feb 2001, dennis roberts wrote in part:
> MTB > ttest 5 c1
>
> One-Sample T: C1
>
> Test of mu = 5 vs mu not = 5
>
> Variable N Mean StDev SE Mean
> C1 20 -0.082 0.914 0.204
>
> Variable 95.0% CI T P
> C1 ( -0.510, 0.345) -24.88 0.000 <<< forget the 0 here
> but, what does this EXACTLY mean?
If the question you're asking is, is this probability determined with
respect to a one-sided or a two-sided alternative hypothesis, the answer
is "two-sided". This is implied by the line above:
> Test of mu = 5 vs mu not = 5
which fairly explicitly states a two-sided alternative.
If you want a one-sided alternative, the subcommand
ALTERNATIVE = +1
specifies (e.g.) a "Test of mu = 5 vs mu > 5"; and
ALTERNATIVE = -1
specifies a "Test of mu = 5 vs. mu < 5".
(The two-sided default test corresponds, I believe, to using
ALTERNATIVE = 0 .)
> MTB > regr c2 1 c1
>
> Regression Analysis: C2 versus C1
>
> The regression equation is
> C2 = 0.316 + 0.368 C1
>
> Predictor Coef SE Coef T P
> Constant 0.3164 0.1957 1.62 0.123 <<<< ???? where does
> it come from???
> C1 0.3676 0.2189 1.68 0.110
Presumably if one were sufficiently curious one could use "CDF 1.62" with
the subcommand "T 18" to see whether the value reported is two-tailed or
one-tailed. I'd bet on two-tailed.
> S = 0.8715 R-Sq = 13.5% R-Sq(adj) = 8.7%
>
> Analysis of Variance
>
> Source DF SS MS F P
> Regression 1 2.1428 2.1428 2.82 0.110 <<<< one or
> two tailed????
With respect to the F distribution, how could it be anything but
one-tailed? This is asking whether the predictor accounts for a
significant amount of the variance in the dependent variable, i.e.
whether the regression MS is significantly LARGER than the residual MS.
> Residual Error 18 13.6723 0.7596
> Total 19 15.8151
----------------------------------------------------------------------
Donald F. Burrill [EMAIL PROTECTED]
348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED]
MSC #29, Plymouth, NH 03264 (603) 535-2597
Department of Mathematics, Boston University [EMAIL PROTECTED]
111 Cummington Street, room 261, Boston, MA 02215 (617) 353-5288
184 Nashua Road, Bedford, NH 03110 (603) 471-7128
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