
Review of Short Phrases and Links 
This Review contains major "KolmogorovSmirnov Test" related terms, short phrases and links grouped together in the form of Encyclopedia article.
Definitions
 The KolmogorovSmirnov test is designed to test the hypothesis that a given data set could have been drawn from a given distribution.
 The KolmogorovSmirnov test is more powerful, if it can be applied.
 The KolmogorovSmirnov test is a nonparametric test and can therefore suffer from low power.
 The KolmogorovSmirnov test is commonly used to test whether the population distribution follows a specified continuous distribution.
 The KolmogorovSmirnov test is considered to be conservative, because the probability of a Type I error is less than the specified a value.
 Summary. The KolmogorovSmirnov test (KStest) tries to determine if two datasets differ significantly.
 KolmogorovSmirnov Test The main problem with test is the choice of number and size of the intervals.
 Figure 6 shows the log 10 (pValues) from the KolmogorovSmirnov test as a function of this average difference in spikein concentration.
 From these results it is possible to see that the KolmogorovSmirnov test is less powerful than the other two tests.
 Channel models are also identified by hypothesis testing using KolmogorovSmirnov test.
 Just as in the KolmogorovSmirnov test, this will be the test statistic.
 The KolmogorovSmirnov test and the chisquare test were introduced.
 Calitz F., An alternative to the KolmogorovSmirnov test for goodness of fit, Commun.
 Examples include the KolmogorovSmirnov test and Wilcoxon signed rank test.
 Normal distribution of data, tested by using a normality test, such as ShapiroWilk and KolmogorovSmirnov test.
 For larger samples, the KolmogorovSmirnov test is recommended by SAS and others.
 To apply the KolmogorovSmirnov test, calculate the cumulative frequency (normalized by the sample size) of the observations as a function of class.
 The goodnessoffit test or the KolmogorovSmirnov test is constructed by using the critical values of the Kolmogorov distribution.
 Lilliefors H., On the KolmogorovSmirnov test for the exponential distribution with mean unknown, JASA, 64, 387389. 1969.
 For each potential value x, the KolmogorovSmirnov test compares the proportion of X1 values less than x with proportion of X2 values less than x.
 KolmogorovSmirnov test of the distribution of one sample.
 The KolmogorovSmirnov test, shown below, compares the cumulative distribution of the data to that of the fitted distribution.
 The outcome of a KolmogorovSmirnov test is a probability, whose distribution is shown below for binned and unbinned data.
 Lilliefors H., On the KolmogorovSmirnov test for normality with mean and variance unknown, JASA, 62, 399402, 1967.
 The null hypothesis for the KolmogorovSmirnov test is that the observed P values are identical to a uniform distribution.
 Perform a KolmogorovSmirnov test of the null hypothesis that the sample x comes from the (continuous) distribution dist.
 The null hypothesis for the KolmogorovSmirnov test is that X has a standard normal distribution.
 There are statistical methods to empirically test that assumption, for example the KolmogorovSmirnov test.
 The KolmogorovSmirnov test can be modified to serve as a goodness of fit test.
 In all cases, the KolmogorovSmirnov test was applied to test for a normal distribution.
 The KolmogorovSmirnov test for goodnessoffit is based on this fact.
KolmogorovSmirnov Test
 Choosing a particular normality test: The KolmogorovSmirnov test is generally less powerful than the tests specifically designed to test for normality.
 The values obtained for the KolmogorovSmirnov test (study of normality of continuous variables) are shown in Table 3.
 Note furthermore, that the KolmogorovSmirnov test is more sensitive at points near the median of the distribution than on its tails.
Categories
 GoodnessOfFit Test
 Nonparametric Test
 Rank Test
 Uniform Distribution
 Test Whether

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