# Boost-Commit :

From: pbristow_at_[hidden]
Date: 2007-09-27 13:28:16

Author: pbristow
Date: 2007-09-27 13:28:15 EDT (Thu, 27 Sep 2007)
New Revision: 39580
URL: http://svn.boost.org/trac/boost/changeset/39580

Log:
Cosmetic - changed bolding a tiny bit.
Text files modified:
sandbox/math_toolkit/libs/math/doc/distributions/students_t_examples.qbk | 16 ++++++++--------
1 files changed, 8 insertions(+), 8 deletions(-)

Modified: sandbox/math_toolkit/libs/math/doc/distributions/students_t_examples.qbk
==============================================================================
--- sandbox/math_toolkit/libs/math/doc/distributions/students_t_examples.qbk (original)
+++ sandbox/math_toolkit/libs/math/doc/distributions/students_t_examples.qbk 2007-09-27 13:28:15 EDT (Thu, 27 Sep 2007)
@@ -266,19 +266,19 @@

`cdf(complement(dist, fabs(t))) < alpha / 2`]]

-[[The Alternative-hypothesis: there is
-*difference* in means]
+[[The Alternative-hypothesis: there
+*is difference* in means]
[Reject if complement of CDF for |t| > significance level / 2:

`cdf(complement(dist, fabs(t))) > alpha / 2`]]

-[[The Alternative-hypothesis: the sample mean is *less* than
+[[The Alternative-hypothesis: the sample mean *is less* than
the true mean.]
[Reject if CDF of t > significance level:

`cdf(dist, t) > alpha`]]

-[[The Alternative-hypothesis: the sample mean is *greater* than
+[[The Alternative-hypothesis: the sample mean *is greater* than
the true mean.]
[Reject if complement of CDF of t > significance level:

@@ -289,7 +289,7 @@
Notice that the comparisons are against `alpha / 2` for a two-sided test
and against `alpha` for a one-sided test]

-Now that we have all the parts in place let's take a look at some
+Now that we have all the parts in place, let's take a look at some
sample output, first using the
[@http://www.itl.nist.gov/div898/handbook/eda/section4/eda428.htm
Heat flow data] from the NIST site. The data set was collected
@@ -597,8 +597,8 @@
Here we've used the absolute value of the t-statistic, because we initially
want to know simply whether there is a difference or not (a two-sided test).
However, we can also test whether the mean of the second sample is greater
-or less than that of the first: all the possible tests are summed up
-in the following table:
+or is less (one-sided test) than that of the first:
+all the possible tests are summed up in the following table:

[table
[[Hypothesis][Test]]
@@ -634,7 +634,7 @@
Most of the rest of the sample program is pretty-printing, so we'll
skip over that, and take a look at the sample output for alpha=0.05
(a 95% probability level). For comparison the dataplot output
-for te same data is in
+for the same data is in
[@http://www.itl.nist.gov/div898/handbook/eda/section3/eda353.htm
section 1.3.5.3] of the __handbook.