From 2dd63f45787b45ec66c3f1f15edac59c8b4408c1 Mon Sep 17 00:00:00 2001 From: Kurt Zenker Date: Thu, 4 Jun 2009 09:41:18 +0000 Subject: CWS-TOOLING: integrate CWS chart37 2009-05-22 09:10:36 +0200 iha r272170 : #i102130# color of pies is not loaded correctly 2009-04-27 17:16:20 +0200 iha r271294 : #i24203# compiler problem 2009-04-27 16:43:21 +0200 iha r271292 : #i101281# missing API documentation for secondary axis title properties 2009-04-27 15:26:05 +0200 hde r271276 : #i100987 2009-04-27 15:24:42 +0200 hde r271273 : #i100987 2009-04-24 15:08:33 +0200 iha r271214 : #i100995# crash with some logarithmic scalings 2009-04-22 18:50:56 +0200 dr r271134 : #i82177# write out deleted point labels 2009-04-22 18:40:48 +0200 iha r271133 : #i101281# missing API documentation for secondary axis title properties 2009-04-22 16:39:42 +0200 dr r271128 : #i82177# extensions for bubble charts 2009-04-22 14:37:00 +0200 dr r271114 : #i82177# import/export data label type and separator 2009-04-22 14:36:24 +0200 dr r271113 : #i82177# import/export data label type and separator 2009-04-21 15:25:26 +0200 dr r271038 : #i82177# import data label type and separator from BIFF8 CHFR records 2009-04-21 14:37:16 +0200 dr r271037 : #i82177# dump BIFF8 chart future records 2009-04-20 17:44:27 +0200 iha r271002 : #i96898# reduce library exports 2009-04-20 13:01:13 +0200 iha r270975 : #i24203# rotate data labels - help ids 2009-04-20 11:40:33 +0200 dr r270969 : #i96600# export of axis scaling/positioning properties 2009-04-16 16:02:31 +0200 dr r270892 : #i69599# keep Y axis left in 3d charts 2009-04-15 18:16:46 +0200 dr r270859 : #i69599# import of axis position settings 2009-04-15 18:16:01 +0200 dr r270858 : #i69599# correct handling of logarithmic crossing axes 2009-04-14 16:27:48 +0200 dr r270794 : #i96599# handle auto axis position on logarithmic axes 2009-04-09 19:59:51 +0200 dr r270722 : #i96599# import axis crossing settings, fix import of logarithmic scaling settings 2009-04-09 18:26:00 +0200 iha r270720 : #i96898# reduce library exports 2009-04-09 15:17:04 +0200 iha r270710 : #i96898# reduce library exports 2009-04-09 10:50:14 +0200 dr r270682 : #i24203# import/export of data label rotation, fixed some other broken stuff too 2009-04-08 16:54:54 +0200 dr r270657 : #i24203# import rotation for data point labels 2009-04-06 18:19:17 +0200 iha r270571 : #i100876# Axis scaling settings dialog wrong after API usage (anys different from double type) 2009-04-06 15:57:05 +0200 iha r270567 : #i100105# #i58585# leftover -> 2009-04-06 15:55:48 +0200 iha r270564 : #i58585# leftover -> 2009-04-02 16:41:07 +0200 iha r270422 : #i99721# remove unused code 2009-04-02 14:29:03 +0200 iha r270407 : #i99721# remove unused code 2009-03-26 10:58:23 +0100 iha r270059 : #i96898# reduce library exports 2009-03-26 10:13:49 +0100 iha r270055 : #i96898# reduce library exports 2009-03-25 09:39:13 +0100 iha r269998 : CWS-TOOLING: rebase CWS chart37 to trunk@269781 (milestone: DEV300:m44) 2009-03-24 17:56:56 +0100 iha r269986 : #i96898# reduce library exports 2009-03-24 16:56:44 +0100 iha r269974 : #i99721# remove unused code 2009-03-24 16:48:48 +0100 iha r269970 : #i89731# remove unused string 2009-03-24 15:44:04 +0100 iha r269961 : remove unused code 2009-03-24 15:22:45 +0100 iha r269959 : remove unused code 2009-03-24 15:17:17 +0100 iha r269957 : remove unused code 2009-03-24 11:14:53 +0100 iha r269923 : #i24203# rotate data labels 2009-03-09 12:10:25 +0100 hde r269076 : #i99300# 2009-03-06 15:56:26 +0100 iha r269011 : #i93953# Source Format for secondary axis without data 2009-02-17 15:59:05 +0100 iha r268177 : avoid warning during build 2009-02-17 15:01:59 +0100 iha r268173 : avoid warning during build 2009-02-13 09:39:03 +0100 ufi r267693 : i96999 2009-02-11 15:12:35 +0100 iha r267604 : removed unused string 2009-02-11 14:00:29 +0100 iha r267600 : #i96999# Corrected wording from 'correlation coefficient' to 'coefficient of determination' 2009-02-11 10:56:45 +0100 iha r267584 : #i89731# typo in resource string 2009-02-11 10:01:29 +0100 iha r267582 : #i89031# compile error on asian windows systems 2009-02-10 16:15:16 +0100 iha r267552 : #i24203# rotate data labels 2009-02-04 18:00:33 +0100 iha r267395 : #i98893# don't export defaults to file 2009-02-04 15:48:15 +0100 iha r267390 : #i92128# asian typography for chart elements 2009-02-04 15:17:41 +0100 iha r267386 : #i92128# asian typography for chart elements 2009-01-30 14:41:10 +0100 iha r267197 : CWS-TOOLING: rebase CWS chart37 to trunk@267171 (milestone: DEV300:m41) --- helpcontent2/source/text/schart/01/04050100.xhp | 221 ++++++++++++------------ 1 file changed, 115 insertions(+), 106 deletions(-) (limited to 'helpcontent2/source') diff --git a/helpcontent2/source/text/schart/01/04050100.xhp b/helpcontent2/source/text/schart/01/04050100.xhp index 2c728ac160..ca27bfda9c 100644 --- a/helpcontent2/source/text/schart/01/04050100.xhp +++ b/helpcontent2/source/text/schart/01/04050100.xhp @@ -1,9 +1,8 @@ - - - + + - - - + + - -Trend Lines -/text/schart/01/04050100.xhp - - - + + Trend Lines + /text/schart/01/04050100.xhp + + + calculating;regression curves -regression curves in charts -trend lines in charts -mean value lines in charts + regression curves in charts + trend lines in charts + mean value lines in charts -Trend Lines + +Trend Lines -Regression curves, also known as trend lines, can be added to all 2D chart types except for Pie and Stock charts. + Regression curves, also known as trend lines, can be added to all 2D chart types except for Pie and Stock charts. -
- -
None -No trend line is shown.Linear -A linear trend line is shown.Logarithmic -A logarithmic trend line is shown.Exponential -An exponential trend line is shown.Power -A power trend line is shown.Show equation -Shows the trend line equation next to the trend line.Show correlation coefficient (R2) -Shows the correlation coefficient next to the trend line. -If you insert a trend line to a chart type that uses categories, like Line or Column, then the numbers 1, 2, 3, … are used as x-values to calculate the trend line. - - -To insert trend lines for all data series, double-click the chart to enter edit mode. Choose Insert - Trend Lines, then select the type of trend line from None, Linear, Logarithmic, Exponential, or Power trend line. - - -To insert a trend line for a single data series, select the data series in the chart, right-click to open the context menu, and choose Insert - Trend Line. - - -To delete a single trend line or mean value line, click the line, then press the Del key. - - -To delete all trend lines, choose Insert - Trend Lines, then select None. - - -A trend line is shown in the legend automatically. +
+ +
None + +No trend line is shown.Linear + +A linear trend line is shown.Logarithmic + +A logarithmic trend line is shown.Exponential + +An exponential trend line is shown.Power + +A power trend line is shown.Show equation + +Shows the trend line equation next to the trend line.Show correlation coefficient (R2) + +Shows the coefficient of determination next to the trend line. + If you insert a trend line to a chart type that uses categories, like Line or Column, then the numbers 1, 2, 3, … are used as x-values to calculate the trend line. + + + To insert trend lines for all data series, double-click the chart to enter edit mode. Choose Insert - Trend Lines, then select the type of trend line from None, Linear, Logarithmic, Exponential, or Power trend line. + + + To insert a trend line for a single data series, select the data series in the chart, right-click to open the context menu, and choose Insert - Trend Line. + + + To delete a single trend line or mean value line, click the line, then press the Del key. + + + To delete all trend lines, choose Insert - Trend Lines, then select None. + + + A trend line is shown in the legend automatically. -Mean Value Lines are special trend lines that show the mean value. Use Insert - Mean Value Lines to insert mean value lines for all data series. A single mean value line can be inserted by the Insert Mean Value Line command of the context menu of a data series. -The trend line has the same color as the corresponding data series. To change the line properties, select the trend line and choose Format - Object Properties - Line. -To show the trend line equation, select the trend line in the chart, right-click to open the context menu, and choose Insert Trend Line Equation. -When the chart is in edit mode, %PRODUCTNAME gives you the equation of the trend line and the correlation coefficient R². Click on the trend line to see the information in the status bar. -For a category chart (for example a line chart), the regression information is calculated using numbers 1, 2, 3, … as x-values. This is also true if your data series uses other numbers as names for the x-values. For such charts the XY chart type might be more suitable. -To show the equation and the correlation coefficient, select the regression curve and choose Format - Object Properties - Equation. see http://specs.openoffice.org/chart/DisplayTrendLineEquations.odthidEnable Show equation to see the equation of the regression curve.hidEnable Show correlation coefficient to see the correlation coefficient of the regression curve. -You can also calculate the parameters using Calc functions as follows. -The linear regression equation -The linear regression follows the equation y=m*x+b. -m = SLOPE(Data_Y;Data_X) -b = INTERCEPT(Data_Y ;Data_X) -Calculate the coefficient of determination by -r² = RSQ(Data_Y;Data_X) -Besides m, b and r² the array function LINEST provides additional statistics for a regression analysis. -The logarithm regression equation -The logarithm regression follows the equation y=a*ln(x)+b. -a = SLOPE(Data_Y;LN(Data_X)) -b = INTERCEPT(Data_Y ;LN(Data_X)) -r² = RSQ(Data_Y;LN(Data_X)) -The exponential regression equation - For exponential regression curves a transformation to a linear model takes place. The optimal curve fitting is related to the linear model and the results are interpreted accordingly. -The exponential regression follows the equation y=b*exp(a*x) or y=b*m^x, which is transformed to ln(y)=ln(b)+a*x or ln(y)=ln(b)+ln(m)*x respectively. -a = SLOPE(LN(Data_Y);Data_X) -The variables for the second variation are calculated as follows: -m = EXP(SLOPE(LN(Data_Y);Data_X)) -b = EXP(INTERCEPT(LN(Data_Y);Data_X)) -Calculate the coefficient of determination by -r² = RSQ(LN(Data_Y);Data_X) -Besides m, b and r² the array function LOGEST provides additional statistics for a regression analysis. -The power regression equation - For power regression curves a transformation to a linear model takes place. The power regression follows the equation y=b*x^a , which is transformed to ln(y)=ln(b)+a*ln(x). -a = SLOPE(LN(Data_Y);LN(Data_X)) -b = EXP(INTERCEPT(LN(Data_Y);LN(Data_X)) -r² = RSQ(LN(Data_Y);LN(Data_X)) -ConstraintsUFI: is this still so? - The calculation of the trend line considers only data pairs with the following values: - - -logarithm regression: only positive x-values are considered, - - -exponential regression: only positive y-values are considered, - - -power regression: only positive x-values and positive y-values are considered. - - -You should transform your data accordingly; it is best to work on a copy of the original data and transform the copied data. -The polynomial regression equation -A polynomial regression curve cannot be added automatically. You must calculate this curve manually. -Create a table with the columns x, x², x³, … , xⁿ, y up to the desired degree n. -Use the formula =LINEST(Data_Y,Data_X) with the complete range x to xⁿ (without headings) as Data_X. -The first row of the LINEST output contains the coefficients of the regression polynomial, with the coefficient of xⁿ at the leftmost position. -The first element of the third row of the LINEST output is the value of r². See the LINEST function for details on proper use and an explanation of the other output parameters. -
-Y Error Bars tab page -
- - + +Mean Value Lines are special trend lines that show the mean value. Use Insert - Mean Value Lines to insert mean value lines for all data series. A single mean value line can be inserted by the Insert Mean Value Line command of the context menu of a data series. + The trend line has the same color as the corresponding data series. To change the line properties, select the trend line and choose Format - Object Properties - Line. + +To show the trend line equation, select the trend line in the chart, right-click to open the context menu, and choose Insert Trend Line Equation. + When the chart is in edit mode, %PRODUCTNAME gives you the equation of the trend line and the coefficient of determination R². Click on the trend line to see the information in the status bar. + For a category chart (for example a line chart), the regression information is calculated using numbers 1, 2, 3, … as x-values. This is also true if your data series uses other numbers as names for the x-values. For such charts the XY chart type might be more suitable. + To show the equation and the coefficient of determination, select the regression curve and choose Format - Object Properties - Equation. see http://specs.openoffice.org/chart/DisplayTrendLineEquations.odthid +Enable Show equation to see the equation of the regression curve.hid +Enable Show Coefficient of Determination to see the determination coefficient of the regression curve. + You can also calculate the parameters using Calc functions as follows. + The linear regression equation + The linear regression follows the equation y=m*x+b. + m = SLOPE(Data_Y;Data_X) + b = INTERCEPT(Data_Y ;Data_X) + Calculate the coefficient of determination by + r² = RSQ(Data_Y;Data_X) + Besides m, b and r² the array function LINEST provides additional statistics for a regression analysis. + The logarithm regression equation + The logarithm regression follows the equation y=a*ln(x)+b. + a = SLOPE(Data_Y;LN(Data_X)) + b = INTERCEPT(Data_Y ;LN(Data_X)) + r² = RSQ(Data_Y;LN(Data_X)) + The exponential regression equation + For exponential regression curves a transformation to a linear model takes place. The optimal curve fitting is related to the linear model and the results are interpreted accordingly. + The exponential regression follows the equation y=b*exp(a*x) or y=b*m^x, which is transformed to ln(y)=ln(b)+a*x or ln(y)=ln(b)+ln(m)*x respectively. + a = SLOPE(LN(Data_Y);Data_X) + The variables for the second variation are calculated as follows: + m = EXP(SLOPE(LN(Data_Y);Data_X)) + b = EXP(INTERCEPT(LN(Data_Y);Data_X)) + Calculate the coefficient of determination by + r² = RSQ(LN(Data_Y);Data_X) + Besides m, b and r² the array function LOGEST provides additional statistics for a regression analysis. + The power regression equation + For power regression curves a transformation to a linear model takes place. The power regression follows the equation y=b*x^a , which is transformed to ln(y)=ln(b)+a*ln(x). + a = SLOPE(LN(Data_Y);LN(Data_X)) + b = EXP(INTERCEPT(LN(Data_Y);LN(Data_X)) + r² = RSQ(LN(Data_Y);LN(Data_X)) + ConstraintsUFI: is this still so? + The calculation of the trend line considers only data pairs with the following values: + + + logarithm regression: only positive x-values are considered, + + + exponential regression: only positive y-values are considered, + + + power regression: only positive x-values and positive y-values are considered. + + + You should transform your data accordingly; it is best to work on a copy of the original data and transform the copied data. + The polynomial regression equation + A polynomial regression curve cannot be added automatically. You must calculate this curve manually. + Create a table with the columns x, x², x³, … , xⁿ, y up to the desired degree n. + Use the formula =LINEST(Data_Y,Data_X) with the complete range x to xⁿ (without headings) as Data_X. + The first row of the LINEST output contains the coefficients of the regression polynomial, with the coefficient of xⁿ at the leftmost position. + The first element of the third row of the LINEST output is the value of r². See the LINEST function for details on proper use and an explanation of the other output parameters. +
+ Y Error Bars tab page +
+ + \ No newline at end of file -- cgit v1.2.3