Trendijooned
Trendijooned saab lisada kõikidele tasapinnalistele diagrammidele, välja arvatud sektor- ja börsidiagrammid.
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.
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To insert a trend line for a data series, select the data series in the chart. Choose
, or right-click to open the context menu, and choose . -
Keskväärtuste jooned on erilised trendijooned, mis näitavad keskväärtust. Andmejadale saab keskväärtuste jooned lisada käsuga
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Trendijoone või keskväärtuste joone kustutamiseks klõpsa joonel ja vajuta Delete-klahvi.
A trend line is shown in the legend automatically. Its name can be defined in options of the trend line.
Trendijoon on sellele vastava andmejadaga sama värvi. Joone omaduste muutmiseks vali esmalt trendijoon ja seejärel vali
.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.
Trendijoone võrrandi kuvamiseks vali diagrammil trendijoon, ava parempoolse nupu klõpsuga kontekstimenüü ja vali .
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
.Default equation uses x for abscissa variable, and f(x) for ordinate variable. To change these names, select the trend line, choose 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
.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
The following regression types are available:
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Linear trend line: regression through equation y=a∙x+b. Intercept b can be forced.
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Polynomial trend line: regression through equation y=Σi(ai∙xi). Intercept a0 can be forced. Degree of polynomial must be given (at least 2).
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Logarithmic trend line: regression through equation y=a∙ln(x)+b.
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Exponential trend line: regression through equation y=b∙exp(a∙x).This equation is equivalent to y=b∙mx with m=exp(a). Intercept b can be forced.
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Power trend line: regression through equation y=b∙xa.
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Moving average trend line: simple moving average is calculated with the n previous y-values, n being the period. No equation is available for this trend line.
Piirangud
Trendijoonte arvutamisel võetakse arvesse ainult järgnevate väärtustega andmete paare:
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Logarithmic trend line: only positive x-values are considered.
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Exponential trend line: only positive y-values are considered, except if all y-values are negative: regression will then follow equation y=-b∙exp(a∙x).
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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 y=-b∙xa.
Sa peaksid oma andmed vastavalt teisendama, kõige kasulikum oleks töötada originaalandmete koopiaga ja teisendada neid.
Calculate Parameters in Calc
Parameetrite arvutamiseks saab kasutada Calc'i funktsioone, nagu järgnevalt kirjeldatud.
Lineaarse regressiooni võrrand
Lineaarne regressioon vastab võrrandile y=m*x+b.
m = SLOPE(y-andmed;x-andmed)
b = INTERCEPT(y-andmed ;x-andmed)
Ahenduskoefitsendi arvutamiseks saab kasutada valemit
r2 = RSQ(y-andmed;x-andmed)
Lisaks m, b ja r2 väärtustele pakub massiivi funktsioon LINEST täiendavat regressioonianalüüsi statistikat.
Logaritmilise regressiooni võrrand
Logaritmiline regressioon vastab võrrandile y=a*ln(x)+b.
a = SLOPE(y-andmed;LN(x-andmed))
b = INTERCEPT(y-andmed ;LN(x-andmed))
r2 = RSQ(LN(y-andmed);LN(x-andmed))
Eksponentsiaalse regressiooni võrrand
Eksponentsiaalsete trendijoonte puhul toimub teisendamine lineaarsele kujule. Kõvera optimaalne sobitamine sõltub lineaarsest kujust ja tulemusi tõlgendatatakse vastavalt.
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(y-andmed);x-andmed)
Teise variandi muutujad arvutatakse järgnevalt:
m = EXP(SLOPE(LN(y-andmed);x-andmed))
b = EXP(INTERCEPT(LN(y-andmed);x-andmed))
Ahenduskoefitsendi arvutamiseks saab kasutada valemit
r2 = RSQ(LN(y-andmed);x-andmed)
Besides m, b and r2 the array function LOGEST provides additional statistics for a regression analysis.
Astmefunktsiooniga määratud regressiooni võrrand
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(y-andmed);LN(x-andmed))
b = EXP(INTERCEPT(LN(y-andmed);LN(x-andmed))
r2 = RSQ(LN(y-andmed);LN(x-andmed))
Polünoomiga määratud regressiooni võrrand
For polynomial regression curves a transformation to a linear model takes place.
Loo tabel veergudega x, x2, x3, … , xn, y kuni soovitud astmeni n.
Kasuta valemit =LINEST(y-andmed; x-andmed) kogu x-andmete vahemiku x kuni xn kohta (ilma päisteta).
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.