Manuals/calci/REGRESSIONANALYSIS - Revision history

Devika: /* See Also */

2018-12-06T20:43:58Z

Devika at 22:25, 10 August 2018

2018-08-10T22:25:51Z

Devika at 19:33, 13 June 2018

2018-06-13T19:33:44Z

Devika: /* Examples */

2018-03-05T19:30:48Z

Examples

Devika: /* Examples */

2018-03-05T19:28:28Z

Examples

Jayaram at 07:34, 13 March 2017

2017-03-13T07:34:10Z

Devika at 20:29, 20 December 2016

2016-12-20T20:29:17Z

Devika at 20:20, 20 December 2016

2016-12-20T20:20:51Z

Devika: Created page with "regreession"

2016-12-20T20:09:56Z

Created page with "regreession"

New page

regreession

@@ Line 109: / Line 109: @@
 | 4  || 82.5 ||	-0.5 ||	-0.8660254037844325
 |}
 ==See Also==

@@ Line 4: / Line 4: @@
 *<math>ConfidenceLevel</math> level of Confidence value.
 *<math>NewTableFlag </math> is either 0 or 1.
 ==Description==

@@ Line 1: / Line 1: @@
-<div style="font-size:30px">'''REGRESSIONANALYSIS (YRange,XRange,ConfidenceLevel,NewTableFlag)'''</div><br/>
+<div style="font-size:25px">'''REGRESSIONANALYSIS (YRange,XRange,ConfidenceLevel,NewTableFlag)'''</div><br/>
 *<math>YRange </math> is the set of dependent variables .
 *<math>XRange </math> is the set of independent variables.
@@ Line 7: / Line 7: @@
 ==Description==
 *This function is calculating the Regression analysis of the given data.
 *This analysis is very useful for the analyzing the large amounts of data and making predictions.
 *Regression analysis is a form of predictive modelling technique which investigates the relationship between a dependent  and independent variable.

@@ Line 80: / Line 80: @@
 | REGRESSION ||1 || 464	|| 464 || 927.9999999999868 ||	0.001075847541170237
 |-
-|RESIDUAL ||2 || 1.0000000000000142 || 0.5000000000000071
+|RESIDUAL ||2 || 1.0000000000000142 || 0.5000000000000071 ||   ||
 |-
-|TOTAL	||3 ||	465
+|TOTAL	||3 ||	465 ||   ||    ||
 |}
 {| class="wikitable"

← Older revision		Revision as of 19:28, 5 March 2018
Line 56:		Line 56:

	=REGRESSIONANALYSIS(A2:A5,B2:B5,0.65,0)		=REGRESSIONANALYSIS(A2:A5,B2:B5,0.65,0)
		+
		+	'''REGRESSION ANALYSIS OUTPUT'''
		+	{\| class="wikitable"
		+	\|+Summary Output
		+	\|-
		+	! Regression Statistics !!
		+	\|-
		+	\| Multiple R \|\| 0.9989241524588297
		+	\|-
		+	\| R Square \|\|0.9978494623655914
		+	\|-
		+	\|ADJUSTEDRSQUARE \|\| 0.996774193548387
		+	\|-
		+	\|STANDARDERROR \|\| 0.7071067811865526
		+	\|-
		+	\|OBSERVATIONS \|\| 4
		+	\|}
		+	{\| class="wikitable"
		+	\|+ANOVA
		+	\|-
		+	! !!DF !!SS!! MS!!F !!SIGNIFICANCE F
		+	\|-
		+	\| REGRESSION \|\|1 \|\| 464 \|\| 464 \|\| 927.9999999999868 \|\| 0.001075847541170237
		+	\|-
		+	\|RESIDUAL \|\|2 \|\| 1.0000000000000142 \|\| 0.5000000000000071
		+	\|-
		+	\|TOTAL \|\|3 \|\| 465
		+	\|}
		+	{\| class="wikitable"
		+	\|-
		+	! !!COEFFICIENTS !!STANDARD ERROR !!T STAT!!P-VALUE!!LOWER 95%!!UPPER 95%
		+	\|-
		+	\|INTERCEPT \|\| 86.5 \|\| 0.6885767430246896 \|\| 125.62143708199342 \|\| 0.00006336233990811291 \|\| 83.53729339698282 \|\| 89.46270660301718
		+	\|-
		+	\|INDEP1 \|\| -4.000000000000007 \|\| 0.1313064328597235 \|\| -30.46309242345547 \|\| 0.0010758475411701829 \|\| -4.564965981777561 \|\| -3.4350340182224532
		+	\|}
		+
		+
		+	{\| class="wikitable"
		+	\|+RESIDUAL OUTPUT
		+	\|-
		+	! OBSERVATION!! PREDICTED Y!! RESIDUALS!! STANDARD RESIDUALS
		+	\|-
		+	\| 1 \|\| 54.49999999999994 \|\| -0.49999999999994316 \|\| -0.8660254037843341
		+	\|-
		+	\| 2 \|\| 62.49999999999996 \|\| 0.5000000000000426 \|\| 0.8660254037845064
		+	\|-
		+	\| 3 \|\| 74.49999999999997 \|\| 0.5000000000000284 \|\| 0.8660254037844818
		+	\|-
		+	\| 4 \|\| 82.5 \|\| -0.5 \|\| -0.8660254037844325
		+	\|}

	==See Also==		==See Also==

← Older revision		Revision as of 07:34, 13 March 2017
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	==References==		==References==
	*[http://en.wikipedia.org/wiki/Regression_analysis Regression Analysis]		*[http://en.wikipedia.org/wiki/Regression_analysis Regression Analysis]
		+
		+
		+
		+	*[[Z_API_Functions \| List of Main Z Functions]]
		+
		+	*[[ Z3 \| Z3 home ]]

← Older revision		Revision as of 20:29, 20 December 2016
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	3.'''Residual output''':		3.'''Residual output''':
	*The residuals show you how far away the actual data points are from the predicted data points.		*The residuals show you how far away the actual data points are from the predicted data points.
		+
		+	==Examples==
		+	1.
		+	{\| class="wikitable"
		+	\|+Spreadsheet
		+	\|-
		+	! !! A !! B
		+	\|-
		+	! 1
		+	\| '''Temperature''' \|\| '''Drying Time(Hrs)'''
		+	\|-
		+	! 2
		+	\| 54 \|\| 8
		+	\|-
		+	! 3
		+	\| 63 \|\| 6
		+	\|-
		+	! 4
		+	\| 75 \|\| 3
		+	\|-
		+	! 5
		+	\| 82 \|\| 1
		+	\|}
		+
		+	=REGRESSIONANALYSIS(A2:A5,B2:B5,0.65,0)
		+
		+	==See Also==
		+	*[[Manuals/calci/SLOPE\| SLOPE]]
		+	*[[Manuals/calci/STEYX\| STEYX]]
		+
		+	==References==
		+	*[http://en.wikipedia.org/wiki/Regression_analysis Regression Analysis]

← Older revision		Revision as of 20:20, 20 December 2016
Line 1:		Line 1:
−	~~regreession~~	+	<div style="font-size:30px">'''REGRESSIONANALYSIS (YRange,XRange,ConfidenceLevel,NewTableFlag)'''</div><br/>
		+	*<math>YRange </math> is the set of dependent variables .
		+	*<math>XRange </math> is the set of independent variables.
		+	*<math>ConfidenceLevel</math> level of Confidence value.
		+	*<math>NewTableFlag </math> is either 0 or 1.
		+
		+	==Description==
		+	*This function is calculating the Regression analysis of the given data.
		+	*This analysis is very useful for the analyzing the large amounts of data and making predictions.
		+	*Regression analysis is a form of predictive modelling technique which investigates the relationship between a dependent and independent variable.
		+	*This technique is used for forecasting, time series modelling and finding the causal effect relationship between the variables.
		+	*This analysis give the result in three table values.
		+	# Regression statistics table.
		+	# ANOVA table.
		+	# Residual output.
		+	1.'''Regression statistics''' :
		+	*It contains multiple R, R Square, Adjusted R Square, Standard Error and observations.
		+	*R square gives the fitness of the data with the regression line.
		+	*That value is closer to 1 is the better the regression line fits the data.
		+	*Standard Error refers to the estimated standard deviation of the error term. It is called the standard error of the regression.
		+	2.'''ANOVA table''':
		+	*ANOVA is the analysis of variance.
		+	*This table splits in to two components which is Residual and Regression.
		+	Total sum of squares = Residual (error) sum of squares + Regression (explained) sum of squares.
		+	*Also this table gives the probability, T stat, significance of F and P.
		+	*When the significance of F is < 0.05, then the result for the given data is statistically significant.
		+	*When the significance of F is > 0.05, then better to stop using this set of independent variables.
		+	*Then remove a variable with a high P-value and return the regression until Significance F drops below 0.05.
		+	*So the Significance of P value should be <0.05.
		+	*This table containing the regression coefficient values also.
		+	3.'''Residual output''':
		+	*The residuals show you how far away the actual data points are from the predicted data points.