X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=doc%2Ftutorial.texi;h=540da62abd90d409219a73ac2004bdba46d11ea6;hb=HEAD;hp=f1cf27219a68e823a6f20baf154622cbf15d725e;hpb=371b97edd5bd56a15a9c3b91f7d526453656b753;p=pspp-builds.git

diff --git a/doc/tutorial.texi b/doc/tutorial.texi
index f1cf2721..540da62a 100644
--- a/doc/tutorial.texi
+++ b/doc/tutorial.texi
@@ -33,7 +33,7 @@ should type.
 
 Throughout this chapter reference is made to a number of sample data files.
 So that you can try the examples for yourself,
-you should have received these files along with your copy of PSPP.
+you should have received these files along with your copy of PSPP.@c
 @footnote{These files contain purely fictitious data.  They should not be used
 for research purposes.}
 @note{Normally these files are installed in the directory
@@ -71,9 +71,9 @@ There are two aspects of data:
 For example, a data set which has the variables @var{height}, @var{weight}, and
 @var{name}, might have the observations:
 @example
-188 89 Ahmed
-119 107 Frank
-123 67 Julie
+1881 89.2 Ahmed
+1192 107.01 Frank
+1230 67 Julie
 @end example
 @noindent
 The following sections explain how to define a dataset.
@@ -639,15 +639,16 @@ is hypothesis testing.
 Researchers commonly need to test hypotheses about a set of data.
 For example, she might want to test whether one set of data comes from
 the same distribution as another,
-or does the mean of a dataset significantly differ from a particular
+or
+whether the mean of a dataset significantly differs from a particular
 value.
 This section presents just some of the possible tests that PSPP offers.
 
 The researcher starts by making a @dfn{null hypothesis}.
 Often this is a hypothesis which he suspects to be false.
 For example, if he suspects that @var{A} is greater than @var{B} he will 
-state the null hypothesis as @math{ @var{A} = @var{B}}.
-@footnote{This example assumes that is it already proven that @var{B} is
+state the null hypothesis as @math{ @var{A} = @var{B}}.@c
+@footnote{This example assumes that it is already proven that @var{B} is
 not greater than @var{A}.}
 
 The @dfn{p-value} is a recurring concept in hypothesis testing.