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
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.
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.
projects / pspp-builds.git / blobdiff