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.hal...@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.hal...@edx.srv.br>
    Tested-by: Olivier Hallot <olivier.hal...@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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