Manuals/calci/KSTESTCORE - Revision history

Devika: /* Examples */

2018-12-06T20:04:17Z

Examples

Devika at 21:39, 14 June 2018

2018-06-14T21:39:20Z

Devika at 21:10, 6 June 2018

2018-06-06T21:10:55Z

Devika at 21:10, 6 June 2018

2018-06-06T21:10:41Z

Jayaram at 07:29, 13 March 2017

2017-03-13T07:29:32Z

Devika at 20:13, 14 December 2016

2016-12-14T20:13:26Z

Devika: /* Description */

2016-12-14T20:01:35Z

Description

Devika at 19:50, 14 December 2016

2016-12-14T19:50:34Z

Devika: Created page with "==Ks"

2016-12-14T19:47:11Z

Created page with "==Ks"

New page

==Ks

← Older revision		Revision as of 20:04, 6 December 2018
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	==Examples==		==Examples==

		+	==Related Videos==
		+
		+	{{#ev:youtube\|v=cltWQsmBg0k&t=108s\|280\|center\|Kolmogorov-Smirnov Test }}

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

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-<div style="font-size:25px">'''KSTESTCORE (XRange,ObservedFrequency,Test,someconfidence,NewTableFlag)'''</div><br/>
+<div style="font-size:25px">'''KSTESTCORE (XRange,ObservedFrequency,Confidence,NewTableFlag,Test,DoMidPointOfIntervals)'''</div><br/>
-*<math>n_1,n_2,n_3...</math> are any real numbers.
 ==Description==

← Older revision		Revision as of 21:10, 6 June 2018
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−	<div style="font-size:~~22px~~">'''KSTESTCORE (XRange,ObservedFrequency,Test,someconfidence,NewTableFlag)'''</div><br/>	+	<div style="font-size:25px">'''KSTESTCORE (XRange,ObservedFrequency,Test,someconfidence,NewTableFlag)'''</div><br/>
	*<math>n_1,n_2,n_3...</math> are any real numbers.		*<math>n_1,n_2,n_3...</math> are any real numbers.

← Older revision		Revision as of 21:10, 6 June 2018
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−	<div style="font-size:~~30px~~">'''KSTESTCORE (XRange,ObservedFrequency,Test,someconfidence,NewTableFlag)'''</div><br/>	+	<div style="font-size:22px">'''KSTESTCORE (XRange,ObservedFrequency,Test,someconfidence,NewTableFlag)'''</div><br/>
	*<math>n_1,n_2,n_3...</math> are any real numbers.		*<math>n_1,n_2,n_3...</math> are any real numbers.

← Older revision		Revision as of 07:29, 13 March 2017
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	==References==		==References==
	[http://www.itl.nist.gov/div898/handbook/eda/section3/eda35g.htm KS Test]		[http://www.itl.nist.gov/div898/handbook/eda/section3/eda35g.htm KS Test]
		+
		+
		+
		+
		+	*[[Z_API_Functions \| List of Main Z Functions]]
		+
		+	*[[ Z3 \| Z3 home ]]

← Older revision		Revision as of 20:13, 14 December 2016
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	==Examples==		==Examples==
		+
		+
		+	==See Also==
		+
		+	*[[Manuals/calci/KSTESTNORMAL\| KSTESTNORMAL]]
		+	*[[Manuals/calci/LEVENESTEST\| LEVENESTEST]]
		+	*[[Manuals/calci/MOODSMEDIANTEST\| MOODSMEDIANTEST]]
		+
		+	==References==
		+	[http://www.itl.nist.gov/div898/handbook/eda/section3/eda35g.htm KS Test]

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 *The Kolmogorov-Smirnov test statistic for the cumulative distribution F(x) is:<math> D_n=Sup_x|F_n(x)-F(x)|</math>where <math>sup_x</math> is the supremum of the set of distances.
 *<math>F_n(x)</math> is the empirical distribution function for n,with the observations <math>X_i</math> is defined as:<math>F_n(x)= Refer Wikipedia I_{X_i\le x}</math>where <math>I_{X_i\le x}</math> is the indicator function, equal to 1 if <math>X_i\le x</math> and equal to 0 otherwise.
 ==Examples==

← Older revision		Revision as of 19:50, 14 December 2016
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−	==Ks	+	<div style="font-size:30px">'''KSTESTCORE (XRange,ObservedFrequency,Test,someconfidence,NewTableFlag)'''</div><br/>
		+	*<math>n_1,n_2,n_3...</math> are any real numbers.
		+
		+	==Description==
		+	*This function gives the test statistic of the K-S test.
		+	*K-S test is indicating the Kolmogorov-Smirnov test.
		+	*It is one of the non parametric test.
		+	*This test is the equality of continuous one dimensional probability distribution.
		+	*It can be used to compare sample with a reference probability distribution or to compare two samples.
		+	*This test statistic measures a distance between the empirical distribution function of the sample and the cumulative distribution function of the reference distribution, or between the empirical distribution functions of two samples.
		+	*The two-sample KS test is one of the most useful and general nonparametric methods for comparing two samples.
		+	*It is sensitive to differences in both location and shape of the empirical cumulative distribution functions of the two samples.
		+	*This test can be modified to serve as a goodness of fit test.
		+	*The assumption of the KS test is:
		+	*Null Hypothesis(H0):The sampled population is normally distributed.
		+	*Alternative hypothesis(Ha):The sampled population is not normally distributed.
		+	*The Kolmogorov-Smirnov test to compare a data set to a given theoretical distribution is as follows:
		+	*1.Data set sorted into increasing order and denoted as <math>x_i</math>, where i=1,...,n.
		+	*2.Smallest empirical estimate of fraction of points falling below <math>x_i</math>, and computed as <math>\frac{(i-1)}{n}</math> for i=1,...,n.
		+	*3.Largest empirical estimate of fraction of points falling below <math>x_i</math> and computed as <math>\frac{i}{n}</math> for i=1,...,n.
		+	*4.Theoretical estimate of fraction of points falling below <math>x_i</math> and computed as <math>F(x_i)</math>, where F(x) is the theoretical distribution function being tested.
		+	*5.Find the absolute value of difference of Smallest and largest empirical value with the theoretical estimation of points.
		+	*This is a measure of "error" for this data point.
		+	*6.From the largest error, we can compute the test statistic.
		+	*The Kolmogorov-Smirnov test statistic for the cumulative distribution F(x) is:<math> D_n=Sup_x\|F_n(x)-F(x)\|</math>where <math>sup_x</math> is the supremum of the set of distances.
		+	*<math>F_n(x)</math> is the empirical distribution function for n,with the observations <math>X_i</math> is defined as:<math>F_n(x)= Refer Wikipedia I_{X_i\le x}</math>where <math>I_{X_i\le x}</math> is the indicator function, equal to 1 if <math>X_i\le x</math> and equal to 0 otherwise.
		+
		+	==Examples==