LibreOffice Help - master/text/schart/01 — Japanese @ TDF Weblate

Translation

Context 04050100.xhp par_id7951902 help.text

English sJhZJ

Japanese

Needs editing

Insufficient privileges for saving translations.

Skip

Context	English	Japanese
04050100.xhp par_id180820161612524298 help.text	<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).
04050100.xhp par_id180820161612525364 help.text	<emph>Logarithmic</emph> trend line: regression through equation <item type="literal">y=a∙ln(x)+b</item>.
04050100.xhp par_id180820161612526680 help.text	<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.
04050100.xhp par_id180820161612527230 help.text	<emph>Power</emph> trend line: regression through equation <item type="literal">y=b∙x</item><sup><item type="literal">a</item></sup>.
04050100.xhp par_id180820161617342768 help.text	<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.
04050100.xhp hd_id9204077 help.text	Constraints	制約
04050100.xhp par_id7393719 help.text	The calculation of the trend line considers only data pairs with the following values:	トレンド線(回帰曲線)の計算は、次の値のデータペアのみを対象に行われます。
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.	このようにして、データを変換します。元のデータはそのまま残しておき、コピーしたデータを使って作業することをお勧めします。
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.	また、次の Calc 関数を使用してパラメーターを計算することもできます。
04050100.xhp hd_id5744193 help.text	The linear regression equation	直線回帰式
04050100.xhp par_id9251991 help.text	The <emph>linear regression</emph> follows the equation <item type="literal">y=m*x+b</item>.	<emph>直線回帰</emph>は、式 <item type="literal">y=m*x+b</item> に従ったものになります。
04050100.xhp par_id7951902 help.text	m = SLOPE(Data_Y;Data_X)	m = SLOPE(Data_Y;Data_X)
04050100.xhp par_id6637165 help.text	b = INTERCEPT(Data_Y ;Data_X)	b = INTERCEPT(Data_Y ;Data_X)
04050100.xhp par_id7879268 help.text	Calculate the coefficient of determination by	決定係数を次の式で計算します:
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	指数回帰式
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.	指数回帰曲線は直線モデルへ変換されます。曲線適合法は線形モデルに関係しているので、その結果も線形モデルに従って解釈されます。
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:	第２変動の変数は次の式で計算されます。:
04050100.xhp par_id7184057 help.text	m = EXP(SLOPE(LN(Data_Y);Data_X))	m = EXP(SLOPE(LN(Data_Y);Data_X))

Loading…

No matching activity found.

Browse all string changes

Things to check

Unchanged translation

Source and translation are identical

Reset

Glossary

English	Japanese
No related strings found in the glossary.

String information

Context

04050100.xhp
par_id7951902
help.text

Source string description

sJhZJ

Source string location

04050100.xhp

String age

4 years ago

Last updated

9 months ago

Source string age

4 years ago

Translation file

ja/helpcontent2/source/text/schart/01.po, string 208