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KOLMOGOROV-SMIRNOV
(ONE SAMPLE TEST)
DEFINITION
? Invented by Vladimic Ivanovich Smirnov(1939)
? The One sample Kolmogorov-smirnov Test procedure
compares the observed cumulative distribution function for
a variable with a specified theoretical distribution, which
may be normal, uniform, poisson or exponential.
? It is used to determine whether two distributions differ or
whether an underlying probability distribution differs from a
hypothesized distribution.
PERFORMING THE KOLMOGOROV-SMIRNOV
ONE SAMPLE TEST
1. Begin by determining the Relative Empirical Frequency
Distribution fxi based on the observed sample. This Relative
Empirical Distribution will approximate a normal distribution. First
find the Midpoint and Standard Deviation.
Formulas:
Midpoint: M= (Xmax+Xmin.)÷2.
Xmax- largest value in the sample
Xmin.- smallest value in the sample
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx
Presentation1-BinomialTest-Chi-SquareTestpptx

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Presentation1-BinomialTest-Chi-SquareTestpptx

  • 2. DEFINITION ? Invented by Vladimic Ivanovich Smirnov(1939) ? The One sample Kolmogorov-smirnov Test procedure compares the observed cumulative distribution function for a variable with a specified theoretical distribution, which may be normal, uniform, poisson or exponential. ? It is used to determine whether two distributions differ or whether an underlying probability distribution differs from a hypothesized distribution.
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