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authorChristian Lohmaier <lohmaier+LibreOffice@googlemail.com>2016-04-16 20:58:46 +0200
committerChristian Lohmaier <lohmaier+LibreOffice@googlemail.com>2016-04-16 20:58:46 +0200
commit1b598faceb47d33dd8c6a7ed73a81bc0d8f8591f (patch)
tree445f48e0e703be388dc2898f3ad4f1f6289eabc9
parenttypo period_lenght → period_length (diff)
downloadhelp-1b598faceb47d33dd8c6a7ed73a81bc0d8f8591f.tar.gz
help-1b598faceb47d33dd8c6a7ed73a81bc0d8f8591f.zip
typo symetric → symmetric
via pootle-feedback Change-Id: I127b9b515d821b3526be629185c2d4853723b8ba
-rw-r--r--source/text/scalc/01/func_forecastetsstatmult.xhp2
1 files changed, 1 insertions, 1 deletions
diff --git a/source/text/scalc/01/func_forecastetsstatmult.xhp b/source/text/scalc/01/func_forecastetsstatmult.xhp
index b739c6e9ca..3741ccb168 100644
--- a/source/text/scalc/01/func_forecastetsstatmult.xhp
+++ b/source/text/scalc/01/func_forecastetsstatmult.xhp
@@ -42,7 +42,7 @@
<embed href="text/scalc/01/exponsmooth_embd.xhp#exampledata"/>
<paragraph id="hd_id04032016185123" role="code" xml-lang="en-US">=FORECAST.ETS.STAT.MULT(Values;Timeline;5;1;TRUE();1)</paragraph>
- <paragraph id="hd_id04032016112394554" role="paragraph" xml-lang="en-US">Returns 0.084073452803966, the multiplicative statistics based on <emph>Values</emph> and <emph>Timeline</emph> named ranges above, with symetric mean absolute percentage error (SMAPE), one sample per period, no missing data, and AVERAGE as aggregation.</paragraph>
+ <paragraph id="hd_id04032016112394554" role="paragraph" xml-lang="en-US">Returns 0.084073452803966, the multiplicative statistics based on <emph>Values</emph> and <emph>Timeline</emph> named ranges above, with symmetric mean absolute percentage error (SMAPE), one sample per period, no missing data, and AVERAGE as aggregation.</paragraph>
<paragraph id="hd_id04032123185123" role="code" xml-lang="en-US">=FORECAST.ETS.STAT.MULT(Values;Timeline;7;1;TRUE();7)</paragraph>
<paragraph id="hd_id040312316112394554" role="paragraph" xml-lang="en-US">Returns 15.8372533480997, the multiplicative statistics based on <emph>Values</emph> and <emph>Timeline</emph> named ranges above, with root mean squared error, no missing data, and SUM as aggregation.</paragraph>
</section>