LibreOffice Help - master/text/schart/01 — Slovak @ TDF Weblate - LibreOffice: a = SLOPE(Data_Y;LN(Data

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Context 04050100.xhp par_id2134159 help.text

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Zundq

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Context	English	Slovak
04050100.xhp par_id7212744 help.text	Logarithmic trend line: only positive x-values are considered.
04050100.xhp par_id1664479 help.text	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>.
04050100.xhp par_id8734702 help.text	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>.
04050100.xhp par_id181279 help.text	You should transform your data accordingly; it is best to work on a copy of the original data and transform the copied data.	Je vhodné najskôr dáta upraviť zodpovedajúcim spôsobom, najlepšie je originálne dáta skopírovať a tie potom ďalej upravovať.
04050100.xhp hd_id180820161528021520 help.text	Calculate Parameters in Calc
04050100.xhp par_id7735221 help.text	You can also calculate the parameters using Calc functions as follows.	Pomocou funkcii aplikácie Calc môžete vypočítať parametre, ako ukazuje následujúce.
04050100.xhp hd_id5744193 help.text	The linear regression equation	Rovnica lineárnej regresie
04050100.xhp par_id9251991 help.text	The <emph>linear regression</emph> follows the equation <item type="literal">y=m*x+b</item>.	<emph>Lineárna regresia</emph> sa riadi rovnicou <item type="literal">y=m*x b</item>.
04050100.xhp par_id7951902 help.text	m = SLOPE(Data_Y;Data_X)	m = SLOPE(Data_Y
04050100.xhp par_id6637165 help.text	b = INTERCEPT(Data_Y ;Data_X)	b = INTERCEPT(Data_Y
04050100.xhp par_id7879268 help.text	Calculate the coefficient of determination by	Determinačný koeficient sa vypočíta ako
04050100.xhp par_id9244361 help.text	r<sup>2</sup> = RSQ(Data_Y;Data_X)
04050100.xhp par_id2083498 help.text	Besides m, b and r<sup>2</sup> the array function <emph>LINEST</emph> provides additional statistics for a regression analysis.
04050100.xhp hd_id2538834 help.text	The logarithmic regression equation
04050100.xhp par_id394299 help.text	The <emph>logarithmic regression</emph> follows the equation <item type="literal">y=a*ln(x)+b</item>.
04050100.xhp par_id2134159 help.text	a = SLOPE(Data_Y;LN(Data_X))	a = SLOPE(Data_Y;LN(Data_X))
04050100.xhp par_id5946531 help.text	b = INTERCEPT(Data_Y ;LN(Data_X))	b = INTERCEPT(Data_Y ;LN(Data_X))
04050100.xhp par_id5649281 help.text	r<sup>2</sup> = RSQ(Data_Y;LN(Data_X))
04050100.xhp hd_id7874080 help.text	The exponential regression equation	Rovnica exponenciálnej regresie
04050100.xhp par_id4679097 help.text	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.	Pre exponenciálne regresné krivky sa použije transformácia na lineárny model. Optimálna krivka zodpovedá lineárnemu modelu a výsledky treba podľa toho interpretovať.
04050100.xhp par_id9112216 help.text	The exponential regression follows the equation <item type="literal">y=bexp(ax)</item> or <item type="literal">y=bm</item><sup><item type="literal">x</item></sup>, which is transformed to <item type="literal">ln(y)=ln(b)+ax</item> or <item type="literal">ln(y)=ln(b)+ln(m)*x</item> respectively.
04050100.xhp par_id4416638 help.text	a = SLOPE(LN(Data_Y);Data_X)	a = SLOPE(LN(Data_Y);Data_X)
04050100.xhp par_id1039155 help.text	The variables for the second variation are calculated as follows:	Premenné druhej variácie sa vypočítajú takto:
04050100.xhp par_id7184057 help.text	m = EXP(SLOPE(LN(Data_Y);Data_X))	m = EXP(SLOPE(LN(Data_Y);Data_X))
04050100.xhp par_id786767 help.text	b = EXP(INTERCEPT(LN(Data_Y);Data_X))	b = EXP(INTERCEPT(LN(Data_Y);Data_X))
04050100.xhp par_id7127292 help.text	Calculate the coefficient of determination by	Determinačný koeficient sa vypočíta ako
04050100.xhp par_id5437177 help.text	r<sup>2</sup> = RSQ(LN(Data_Y);Data_X)
04050100.xhp par_id6946317 help.text	Besides m, b and r<sup>2</sup> the array function <emph>LOGEST</emph> provides additional statistics for a regression analysis.
04050100.xhp hd_id6349375 help.text	The power regression equation	Rovnica mocninovej regresie
04050100.xhp par_id1857661 help.text	For <emph>power regression</emph> curves a transformation to a linear model takes place. The power regression follows the equation <item type="literal">y=bx</item><sup><item type="literal">a</item></sup>, which is transformed to <item type="literal">ln(y)=ln(b)+aln(x)</item>.
04050100.xhp par_id8517105 help.text	a = SLOPE(LN(Data_Y);LN(Data_X))	a = SLOPE(LN(Data_Y);LN(Data_X))

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English	Slovak
Ln	Riad.	LibreOffice UI - master
SLOPE	SLOPE	LibreOffice UI - master
Slope	Smernica	LibreOffice UI - master

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Context

04050100.xhp
par_id2134159
help.text

Source string description

Zundq

Source string location

04050100.xhp

String age

5 years ago

Last updated

a year ago

Source string age

5 years ago

Translation file

sk/helpcontent2/source/text/schart/01.po, string 212