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  Encyclopedia of Keywords > Goodness-Of-Fit Test > Kolmogorov-Smirnov Test   Michael Charnine

Keywords and Sections
KS-TEST
CHOICE
FUNCTION
TESTS
HYPOTHESIS TESTING
TEST STATISTIC
CHI-SQUARE TEST
GOODNESS
RANK TEST
DATA
LARGER SAMPLES
SAMPLE SIZE
CRITICAL VALUES
EXPONENTIAL DISTRIBUTION
POTENTIAL VALUE
DISTRIBUTION
NORMALITY
NULL HYPOTHESIS
TEST
GOODNESS-OF-FIT
KOLMOGOROV-SMIRNOV TEST
Review of Short Phrases and Links

    This Review contains major "Kolmogorov-Smirnov Test"- related terms, short phrases and links grouped together in the form of Encyclopedia article.

Definitions

  1. The Kolmogorov-Smirnov test is designed to test the hypothesis that a given data set could have been drawn from a given distribution.
  2. The Kolmogorov-Smirnov test is more powerful, if it can be applied.
  3. The Kolmogorov-Smirnov test is a nonparametric test and can therefore suffer from low power.
  4. The Kolmogorov-Smirnov test is commonly used to test whether the population distribution follows a specified continuous distribution.
  5. The Kolmogorov-Smirnov test is considered to be conservative, because the probability of a Type I error is less than the specified a -value.

Ks-Test

  1. Summary. The Kolmogorov-Smirnov test (KS-test) tries to determine if two datasets differ significantly.

Choice

  1. Kolmogorov-Smirnov Test The main problem with test is the choice of number and size of the intervals.

Function

  1. Figure 6 shows the -log 10 (pValues) from the Kolmogorov-Smirnov test as a function of this average difference in spike-in concentration.

Tests

  1. From these results it is possible to see that the Kolmogorov-Smirnov test is less powerful than the other two tests.

Hypothesis Testing

  1. Channel models are also identified by hypothesis testing using Kolmogorov-Smirnov test.

Test Statistic

  1. Just as in the Kolmogorov-Smirnov test, this will be the test statistic.

Chi-Square Test

  1. The Kolmogorov-Smirnov test and the chi-square test were introduced.

Goodness

  1. Calitz F., An alternative to the Kolmogorov-Smirnov test for goodness of fit, Commun.

Rank Test

  1. Examples include the Kolmogorov-Smirnov test and Wilcoxon signed rank test.

Data

  1. Normal distribution of data, tested by using a normality test, such as Shapiro-Wilk and Kolmogorov-Smirnov test.

Larger Samples

  1. For larger samples, the Kolmogorov-Smirnov test is recommended by SAS and others.

Sample Size

  1. To apply the Kolmogorov-Smirnov test, calculate the cumulative frequency (normalized by the sample size) of the observations as a function of class.

Critical Values

  1. The goodness-of-fit test or the Kolmogorov-Smirnov test is constructed by using the critical values of the Kolmogorov distribution.

Exponential Distribution

  1. Lilliefors H., On the Kolmogorov-Smirnov test for the exponential distribution with mean unknown, JASA, 64, 387-389. 1969.

Potential Value

  1. For each potential value x, the Kolmogorov-Smirnov test compares the proportion of X1 values less than x with proportion of X2 values less than x.

Distribution

  1. Kolmogorov-Smirnov test of the distribution of one sample.
  2. The Kolmogorov-Smirnov test, shown below, compares the cumulative distribution of the data to that of the fitted distribution.
  3. The outcome of a Kolmogorov-Smirnov test is a probability, whose distribution is shown below for binned and unbinned data.

Normality

  1. Lilliefors H., On the Kolmogorov-Smirnov test for normality with mean and variance unknown, JASA, 62, 399-402, 1967.

Null Hypothesis

  1. The null hypothesis for the Kolmogorov-Smirnov test is that the observed P values are identical to a uniform distribution.
  2. Perform a Kolmogorov-Smirnov test of the null hypothesis that the sample x comes from the (continuous) distribution dist.
  3. The null hypothesis for the Kolmogorov-Smirnov test is that X has a standard normal distribution.

Test

  1. There are statistical methods to empirically test that assumption, for example the Kolmogorov-Smirnov test.
  2. The Kolmogorov-Smirnov test can be modified to serve as a goodness of fit test.
  3. In all cases, the Kolmogorov-Smirnov test was applied to test for a normal distribution.

Goodness-Of-Fit

  1. The Kolmogorov-Smirnov test for goodness-of-fit is based on this fact.

Kolmogorov-Smirnov Test

  1. Choosing a particular normality test: The Kolmogorov-Smirnov test is generally less powerful than the tests specifically designed to test for normality.
  2. The values obtained for the Kolmogorov-Smirnov test (study of normality of continuous variables) are shown in Table 3.
  3. Note furthermore, that the Kolmogorov-Smirnov test is more sensitive at points near the median of the distribution than on its tails.

Categories

  1. Goodness-Of-Fit Test
  2. Nonparametric Test
  3. Rank Test
  4. Uniform Distribution
  5. Test Whether
  6. Books about "Kolmogorov-Smirnov Test" in Amazon.com

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  Originally created: August 16, 2007.
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