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| -rw-r--r-- | source/text/scalc/01/statistics_regression.xhp | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/source/text/scalc/01/statistics_regression.xhp b/source/text/scalc/01/statistics_regression.xhp index a217084c58..26ec722534 100644 --- a/source/text/scalc/01/statistics_regression.xhp +++ b/source/text/scalc/01/statistics_regression.xhp @@ -52,7 +52,7 @@ <list type="unordered"> <listitem> - <paragraph id="par_id1701201620334364" role="ul_item" xml-lang="en-US"><emph>Linear Regression</emph>: find a strait line in the form of <item type="literal">y = a.x + b</item>, where <item type="literal">a</item> is the slope and <item type="literal">b</item> is the intercept that best fits the data.</paragraph> + <paragraph id="par_id1701201620334364" role="ul_item" xml-lang="en-US"><emph>Linear Regression</emph>: find a straight line in the form of <item type="literal">y = a.x + b</item>, where <item type="literal">a</item> is the slope and <item type="literal">b</item> is the intercept that best fits the data.</paragraph> </listitem> <listitem> <paragraph id="par_id1701201620340168" role="ul_item" xml-lang="en-US"><emph>Logarithmic regression</emph>: find a logarithmic curve in the form of <item type="literal">y = a.ln(x) + b</item>, where <item type="literal">a</item> is the slope, <item type="literal">b</item> is the intercept and <item type="literal">ln(x)</item> is the natural logarithm of <item type="literal">x</item>, that best fits the data.</paragraph> |