[Libreoffice-commits] help.git: source/text
Olivier Hallot
olivier.hallot at libreoffice.org
Sun Jul 23 21:34:34 UTC 2017
source/text/scalc/guide/autofilter.xhp | 2 +-
source/text/schart/01/04050100.xhp | 18 +++++++++---------
2 files changed, 10 insertions(+), 10 deletions(-)
New commits:
commit 768ebf50c5564dc4ecbde7af8dd136c4acdf87f4
Author: Olivier Hallot <olivier.hallot at libreoffice.org>
Date: Sat Jul 22 12:23:36 2017 -0300
Fix some DTD issues in Help Pages
<item> does not have child nodes
Change-Id: Ieac002b65cfc54c66af92e1a7cb80a1fc7ce31f4
Reviewed-on: https://gerrit.libreoffice.org/40313
Reviewed-by: Olivier Hallot <olivier.hallot at edx.srv.br>
Tested-by: Olivier Hallot <olivier.hallot at edx.srv.br>
diff --git a/source/text/scalc/guide/autofilter.xhp b/source/text/scalc/guide/autofilter.xhp
index 46b226634..8e605f976 100644
--- a/source/text/scalc/guide/autofilter.xhp
+++ b/source/text/scalc/guide/autofilter.xhp
@@ -52,7 +52,7 @@
</listitem>
</list>
<paragraph xml-lang="en-US" id="par_id9216589" role="paragraph">When you apply an additional AutoFilter on another column of a filtered data range, then the other combo boxes list only the filtered data.</paragraph>
- <paragraph xml-lang="en-US" id="par_id3153714" role="paragraph">To display all records again, select the <emph>all</emph> entry in the AutoFilter combo box. If you choose "Standard<emph>"</emph>, the <item type="menuitem">Standard Filter</item> dialog appears, allowing you to set up a standard filter. Choose "Top 10" to display the highest 10 values only. </paragraph>
+ <paragraph xml-lang="en-US" id="par_id3153714" role="paragraph">To display all records again, select the <emph>all</emph> entry in the AutoFilter combo box. If you choose <emph>Standard</emph>, the <item type="menuitem">Standard Filter</item> dialog appears, allowing you to set up a standard filter. Choose "Top 10" to display the highest 10 values only. </paragraph>
<paragraph xml-lang="en-US" id="par_id3147340" role="paragraph">To stop using AutoFilter, reselect all cells selected in step 1 and once again choose <emph>Data - Filter - AutoFilter</emph>.</paragraph>
<paragraph xml-lang="en-US" id="par_id4303415" role="tip">To assign different AutoFilters to different sheets, you must first define a database range on each sheet.</paragraph>
<paragraph xml-lang="en-US" id="par_id3159236" role="warning">The arithmetic functions also take account of the cells that are not visible due to an applied filter. For example, a sum of an entire column will also total the values in the filtered cells. Apply the <link href="text/scalc/01/04060106.xhp" name="SUBTOTAL">SUBTOTAL</link> function if only the cells visible after the application of a filter are to be taken into account.</paragraph>
diff --git a/source/text/schart/01/04050100.xhp b/source/text/schart/01/04050100.xhp
index 1b5302880..8b863cd93 100644
--- a/source/text/schart/01/04050100.xhp
+++ b/source/text/schart/01/04050100.xhp
@@ -102,7 +102,7 @@
<paragraph id="par_id8962066" role="paragraph" xml-lang="en-US">To change format of values (use less significant digits or scientific notation), select the equation in the chart, right-click to open the context menu, and choose <item type="menuitem">Format Trend Line Equation - Numbers</item>.</paragraph>
<paragraph id="par_id180820161627109994" role="paragraph" xml-lang="en-US">Default equation uses <item type="literal">x</item> for abscissa variable, and <item type="literal">f(x)</item> for ordinate variable. To change these names, select the trend line, choose <item type="menuitem">Format - Format Selection – Type</item> and enter names in <item type="literal">X Variable Name</item> and <item type="literal">Y Variable Name</item> edit boxes.</paragraph>
<bookmark xml-lang="en-US" branch="hid/.uno:InsertR2Value" id="bm_id2754602" localize="false"/>
-<paragraph id="par_id18082016163702791" role="paragraph" xml-lang="en-US">To show the coefficient of determination R<sup>2</sup>, select the equation in the chart, right-click to open the context menu, and choose <item type="menuitem">Insert R</item><item type="menuitem">2</item>.</paragraph>
+<paragraph id="par_id18082016163702791" role="paragraph" xml-lang="en-US">To show the coefficient of determination R<sup>2</sup>, select the equation in the chart, right-click to open the context menu, and choose <item type="menuitem">Insert R</item><sup><item type="menuitem">2</item></sup>.</paragraph>
<paragraph id="par_id180820161637028632" role="note" xml-lang="en-US">If intercept is forced, coefficient of determination R<sup>2</sup> is not calculated in the same way as with free intercept. R<sup>2</sup> values can not be compared with forced or free intercept.</paragraph>
<paragraph id="hd_id180820161534333509" role="heading" level="2" xml-lang="en-US">Trend Lines Curve Types</paragraph>
@@ -113,16 +113,16 @@
<paragraph id="par_id180820161604098009" role="paragraph" xml-lang="en-US"><emph>Linear</emph> trend line: regression through equation <item type="literal">y=a∙x+b</item>. Intercept <item type="literal">b</item> can be forced.</paragraph>
</listitem>
<listitem>
- <paragraph id="par_id180820161612524298" role="paragraph" xml-lang="en-US"><emph>Polynomial</emph> trend line: regression through equation <item type="literal">y=Σ(a</item><item type="literal">i</item><item type="literal">∙x</item><item type="literal">i</item><item type="literal">)</item>. Intercept <item type="literal">a</item><item type="literal">0</item> can be forced. Degree of polynomial must be given (at least 2).</paragraph>
+ <paragraph id="par_id180820161612524298" role="paragraph" xml-lang="en-US"><emph>Polynomial</emph> trend line: regression through equation <item type="literal">y=Σ</item><sub><item type="literal">i</item></sub><item type="literal">(a</item><sub><item type="literal">i</item></sub><item type="literal">∙x</item><sup><item type="literal">i</item></sup><item type="literal">)</item>. Intercept <item type="literal">a</item><sub><item type="literal">0</item></sub> can be forced. Degree of polynomial must be given (at least 2).</paragraph>
</listitem>
<listitem>
<paragraph id="par_id180820161612525364" role="paragraph" xml-lang="en-US"><emph>Logarithmic</emph> trend line: regression through equation <item type="literal">y=a∙ln(x)+b</item>.</paragraph>
</listitem>
<listitem>
- <paragraph id="par_id180820161612526680" role="paragraph" xml-lang="en-US"><emph>Exponential</emph> trend line: regression through equation <item type="literal">y=b∙exp(a∙x)</item>.This equation is equivalent to <item type="literal">y=b∙m</item><item type="literal">x</item> with <item type="literal">m=exp(a)</item>. Intercept <item type="literal">b</item> can be forced.</paragraph>
+ <paragraph id="par_id180820161612526680" role="paragraph" xml-lang="en-US"><emph>Exponential</emph> trend line: regression through equation <item type="literal">y=b∙exp(a∙x)</item>.This equation is equivalent to <item type="literal">y=b∙m</item><sup><item type="literal">x</item></sup> with <item type="literal">m=exp(a)</item>. Intercept <item type="literal">b</item> can be forced.</paragraph>
</listitem>
<listitem>
- <paragraph id="par_id180820161612527230" role="paragraph" xml-lang="en-US"><emph>Power</emph> trend line: regression through equation <item type="literal">y=b∙x</item><item type="literal">a</item>.</paragraph>
+ <paragraph id="par_id180820161612527230" role="paragraph" xml-lang="en-US"><emph>Power</emph> trend line: regression through equation <item type="literal">y=b∙x</item><sup><item type="literal">a</item></sup>.</paragraph>
</listitem>
<listitem>
<paragraph id="par_id180820161617342768" role="paragraph" xml-lang="en-US"><emph>Moving average</emph> trend line: simple moving average is calculated with the <emph>n</emph> previous y-values, <emph>n</emph> being the period. No equation is available for this trend line.</paragraph>
@@ -139,7 +139,7 @@
<paragraph id="par_id1664479" role="paragraph" xml-lang="en-US">Exponential trend line: only positive y-values are considered, except if all y-values are negative: regression will then follow equation <item type="literal">y=-b∙exp(a∙x)</item>.</paragraph>
</listitem>
<listitem>
- <paragraph id="par_id8734702" role="paragraph" xml-lang="en-US">Power trend line: only positive x-values are considered; only positive y-values are considered, except if all y-values are negative: regression will then follow equation<item type="literal"> y=-b∙x</item><item type="literal">a</item>.</paragraph>
+ <paragraph id="par_id8734702" role="paragraph" xml-lang="en-US">Power trend line: only positive x-values are considered; only positive y-values are considered, except if all y-values are negative: regression will then follow equation<item type="literal"> y=-b∙x</item><sup><item type="literal">a</item></sup>.</paragraph>
</listitem></list>
<paragraph id="par_id181279" role="paragraph" xml-lang="en-US">You should transform your data accordingly; it is best to work on a copy of the original data and transform the copied data.</paragraph>
@@ -162,7 +162,7 @@
<paragraph id="hd_id7874080" role="heading" level="3" xml-lang="en-US">The exponential regression equation</paragraph>
<paragraph id="par_id4679097" role="paragraph" xml-lang="en-US"> For exponential trend lines a transformation to a linear model takes place. The optimal curve fitting is related to the linear model and the results are interpreted accordingly.</paragraph>
-<paragraph id="par_id9112216" role="paragraph" xml-lang="en-US">The exponential regression follows the equation <item type="literal">y=b*exp(a*x)</item> or <item type="literal">y=b*m</item><sup>x</sup>, which is transformed to <item type="literal">ln(y)=ln(b)+a*x</item> or <item type="literal">ln(y)=ln(b)+ln(m)*x</item> respectively.</paragraph>
+<paragraph id="par_id9112216" role="paragraph" xml-lang="en-US">The exponential regression follows the equation <item type="literal">y=b*exp(a*x)</item> or <item type="literal">y=b*m</item><sup><item type="literal">x</item></sup>, which is transformed to <item type="literal">ln(y)=ln(b)+a*x</item> or <item type="literal">ln(y)=ln(b)+ln(m)*x</item> respectively.</paragraph>
<paragraph id="par_id4416638" role="code" xml-lang="en-US">a = SLOPE(LN(Data_Y);Data_X) </paragraph>
<paragraph id="par_id1039155" role="paragraph" xml-lang="en-US">The variables for the second variation are calculated as follows:</paragraph>
<paragraph id="par_id7184057" role="code" xml-lang="en-US">m = EXP(SLOPE(LN(Data_Y);Data_X)) </paragraph>
@@ -172,7 +172,7 @@
<paragraph id="par_id6946317" role="paragraph" xml-lang="en-US">Besides m, b and r<sup>2</sup> the array function <emph>LOGEST</emph> provides additional statistics for a regression analysis.</paragraph>
<paragraph id="hd_id6349375" role="heading" level="3" xml-lang="en-US">The power regression equation</paragraph>
-<paragraph id="par_id1857661" role="paragraph" xml-lang="en-US"> For <emph>power regression</emph> curves a transformation to a linear model takes place. The power regression follows the equation <item type="literal">y=b*x^a</item> , which is transformed to <item type="literal">ln(y)=ln(b)+a*ln(x)</item>.</paragraph>
+<paragraph id="par_id1857661" role="paragraph" xml-lang="en-US"> For <emph>power regression</emph> curves a transformation to a linear model takes place. The power regression follows the equation <item type="literal">y=b*x</item><sup><item type="literal">a</item></sup>, which is transformed to <item type="literal">ln(y)=ln(b)+a*ln(x)</item>.</paragraph>
<paragraph id="par_id8517105" role="code" xml-lang="en-US">a = SLOPE(LN(Data_Y);LN(Data_X)) </paragraph>
<paragraph id="par_id9827265" role="code" xml-lang="en-US">b = EXP(INTERCEPT(LN(Data_Y);LN(Data_X)) </paragraph>
<paragraph id="par_id2357249" role="code" xml-lang="en-US">r<sup>2</sup> = RSQ(LN(Data_Y);LN(Data_X)) </paragraph>
@@ -181,7 +181,7 @@
<paragraph id="par_id8918729" role="paragraph" xml-lang="en-US">For <emph>polynomial regression</emph> curves a transformation to a linear model takes place.</paragraph>
<paragraph id="par_id33875" role="paragraph" xml-lang="en-US">Create a table with the columns x, x<sup>2</sup>, x<sup>3</sup>, … , x<sup>n</sup>, y up to the desired degree n. </paragraph>
<paragraph id="par_id8720053" role="paragraph" xml-lang="en-US">Use the formula <item type="literal">=LINEST(Data_Y,Data_X)</item> with the complete range x to x<sup>n</sup> (without headings) as Data_X. </paragraph>
-<paragraph id="par_id5068514" role="paragraph" xml-lang="en-US">The first row of the <emph>LINEST</emph> output contains the coefficients of the regression polynomial, with the coefficient of xⁿ at the leftmost position.</paragraph>
+<paragraph id="par_id5068514" role="paragraph" xml-lang="en-US">The first row of the <emph>LINEST</emph> output contains the coefficients of the regression polynomial, with the coefficient of x<sup>n</sup> at the leftmost position.</paragraph>
<paragraph id="par_id8202154" role="paragraph" xml-lang="en-US">The first element of the third row of the <emph>LINEST</emph> output is the value of r<sup>2</sup>. See the <link href="text/scalc/01/04060107.xhp#Section8"><emph>LINEST</emph></link> function for details on proper use and an explanation of the other output parameters.</paragraph>
<section id="relatedtopics">
@@ -194,4 +194,4 @@
</section>
</body>
-</helpdocument>
\ No newline at end of file
+</helpdocument>
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