Apache
/
commons-math
mirror of https://github.com/apache/commons-math.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Fixed typos. 

git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@141195 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2004-04-26 05:16:35 +00:00
parent 7c918e3c65
commit aff4070d66
1 changed files with 4 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
xdocs/userguide/stat.xml
View File

@ -17,7 +17,7 @@
--> -->
<?xml-stylesheet type="text/xsl" href="./xdoc.xsl"?> <?xml-stylesheet type="text/xsl" href="./xdoc.xsl"?>
<!-- $Revision: 1.14 $ $Date: 2004/04/25 19:16:13 $ --> <!-- $Revision: 1.15 $ $Date: 2004/04/26 05:16:35 $ -->
<document url="stat.html"> <document url="stat.html">
<properties> <properties>
<title>The Commons Math User Guide - Statistics</title> <title>The Commons Math User Guide - Statistics</title>
@ -243,7 +243,7 @@ System.out.println(f.getCumPct("z")); // displays 1 -- last value
<p> <p>
<a href="../apidocs/org/apache/commons/math/stat/multivariate/BivariateRegression.html"> <a href="../apidocs/org/apache/commons/math/stat/multivariate/BivariateRegression.html">
org.apache.commons.math.stat.multivariate.BivariateRegression</a> org.apache.commons.math.stat.multivariate.BivariateRegression</a>
provides ordinary least squares regression with one independent variable., estimating provides ordinary least squares regression with one independent variable, estimating
the linear model: the linear model:
</p> </p>
<p> <p>
@ -317,7 +317,7 @@ System.out.println(regression.getSlopeStdErr()); // displays slope standard erro
<source> <source>
System.out.println(regression.predict(1.5d) // displays predicted y value for x = 1.5 System.out.println(regression.predict(1.5d) // displays predicted y value for x = 1.5
</source> </source>
More data points can be added and subsequent getXXX calls will incorporate More data points can be added and subsequent getXxx calls will incorporate
additional data in statistics. additional data in statistics.
</dd> </dd>
<dt>Estimate a model from a double[][] array of data points</dt> <dt>Estimate a model from a double[][] array of data points</dt>
@ -336,7 +336,7 @@ System.out.println(regression.getSlope()); // displays slope of regression
System.out.println(regression.getSlopeStdErr()); // displays slope standard error System.out.println(regression.getSlopeStdErr()); // displays slope standard error
</source> </source>
More data points -- even another double[][] array -- can be added and subsequent More data points -- even another double[][] array -- can be added and subsequent
getXXX calls will incorporate additional data in statistics. getXxx calls will incorporate additional data in statistics.
</dd> </dd>
</dl> </dl>
</p> </p>