X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=doc%2Ftutorial.texi;h=994c0a7fc90028e5ffab058d92b3849aaf2520d0;hb=2fc70481c7621ee4d51f986c53c4add4ec6cc57d;hp=8ddb159bae1b2da86a0b5ff774311d2364e6878c;hpb=17a7fef26d9f85af20e9a201690c769406171d26;p=pspp

diff --git a/doc/tutorial.texi b/doc/tutorial.texi
index 8ddb159bae..994c0a7fc9 100644
--- a/doc/tutorial.texi
+++ b/doc/tutorial.texi
@@ -507,7 +507,7 @@ Output (dictionary information omitted for clarity):
 
 1.2 RELIABILITY.  Reliability Statistics
 #================#==========#
-#Cronbach's Alpha#N of items#
+#Cronbach's Alpha#N of Items#
 #================#==========#
 #             .86#         3#
 #================#==========#
@@ -648,7 +648,7 @@ 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}}.@c
-@footnote{This example assumes that is it already proven that @var{B} is
+@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.