Fix missing @clicksequence problem with older Texinfo versions.

[pspp-builds.git] / doc / regression.texi

diff --git a/doc/regression.texi b/doc/regression.texi
index 66125b48da25519544cc3bf4724978f0da8d0466..b47416b70191c1a1af0129ca073a36fa7a390056 100644 (file)
--- a/doc/regression.texi
+++ b/doc/regression.texi
@@ -9,25 +9,25 @@ estimation. The procedure is appropriate for data which satisfy those
 assumptions typical in linear regression:
 
 @itemize @bullet
-@item The data set contains n observations of a dependent variable, say
-Y_1,...,Y_n, and n observations of one or more explanatory
-variables. Let X_11, X_12, ..., X_1n denote the n observations of the
-first explanatory variable; X_21,...,X_2n denote the n observations of the
-second explanatory variable; X_k1,...,X_kn denote the n observations of the kth
+@item The data set contains @math{n} observations of a dependent variable, say
+@math{Y_1,@dots{},Y_n}, and @math{n} observations of one or more explanatory
+variables. Let @math{X_{11}, X_{12}}, @dots{}, @math{X_{1n}} denote the @math{n} observations of the
+first explanatory variable; @math{X_{21}},@dots{},@math{X_{2n}} denote the @math{n} observations of the
+second explanatory variable; @math{X_{k1}},@dots{},@math{X_{kn}} denote the @math{n} observations of the kth
 explanatory variable.
 
-@item The dependent variable Y has the following relationship to the 
+@item The dependent variable @math{Y} has the following relationship to the 
 explanatory variables:
 @math{Y_i = b_0 + b_1 X_{1i} + ... + b_k X_{ki} + Z_i} 
-where @math{b_0, b_1, ..., b_k} are unknown
-coefficients, and @math{Z_1,...,Z_n} are independent, normally
-distributed ``noise'' terms with common variance. The noise, or
+where @math{b_0, b_1, @dots{}, b_k} are unknown
+coefficients, and @math{Z_1,@dots{},Z_n} are independent, normally
+distributed ``noise'' terms with mean zero and common variance. The noise, or
 ``error'' terms are unobserved. This relationship is called the
 ``linear model.''
 @end itemize
 
 The REGRESSION procedure estimates the coefficients
-@math{b_0,...,b_k} and produces output relevant to inferences for the
+@math{b_0,@dots{},b_k} and produces output relevant to inferences for the
 linear model. 
 
 @c If you add any new commands, then don't forget to remove the entry in 
@@ -110,4 +110,3 @@ list.
 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 
            /save pred resid /method=enter.
 @end example
-@setfilename ignored