Liñas de tendencia

Pódense engadir liñas de tendencia a todos os tipos de gráficas en 2D, excepto as de sector e de cotizacións

Para acceder a esta orde...

Escolla Inserir - Liña de tendencia (Gráficas)


Icona Nota

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. For such charts the XY chart type might be more suitable.


Icona Nota

A trend line is shown in the legend automatically. Its name can be defined in options of the trend line.


The trend line has the same color as the corresponding data series. To change the line properties, select the trend line and choose Format - Format Selection - Line.

Trend Line Equation and Coefficient of Determination

When the chart is in edit mode, LibreOffice gives you the equation of the trend line and the coefficient of determination R2, even if they are not shown: click on the trend line to see the information in the status bar.

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.

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 Format Trend Line Equation - Numbers.

Default equation uses x for abscissa variable, and f(x) for ordinate variable. To change these names, select the trend line, choose Format - Format Selection – Type and enter names in X Variable Name and Y Variable Name edit boxes.

To show the coefficient of determination R2, select the equation in the chart, right-click to open the context menu, and choose Insert R2.

Icona Nota

If intercept is forced, coefficient of determination R2 is not calculated in the same way as with free intercept. R2 values can not be compared with forced or free intercept.


Trend Lines Curve Types

Están dispoñíbeis os tipos de regresión seguintes:

Restricións

O cálculo da liña de tendencia considera só pares de datos cos valores seguintes:

Ten que transformar os seus datos de acordo con isto; é mellor traballar cunha copia dos datos orixinais e transformar os datos copiados.

Calcular parámetros no Calc

Tamén pode calcular os parámetros empregando as funcións do Calc como segue.

A ecuación de regresión lineal

A regresión lineal segue a ecuación 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 logarithmic regression equation

The logarithmic 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))

A ecuación de regresión exponencial

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.

The exponential regression follows the equation y=b*exp(a*x) or y=b*mx, 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*xa, 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))

A ecuación de regresión polinomial

Para curvas de regresión polinomial realízase unha transformación a un modelo lineal.

Crear unha táboa coas columnas x, x2, x3, … , xn, y até o grao desexado 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.

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