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How do you interpret a KSL or Kolmogorov Smirnov Lilliefors test?
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An Elisa Test is used to test for a substance using antibodies for colour change. The test has been used in medicine and plants. Performing the test involves using an antibody and enzymes.
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What nonparametric test does not have comparable parametric test?
A classic would be the Kolmogorov-Smirnov test.
How do you know if measurements are poisson distributed?
The Kolmogorov-Smirnov one sample test.
Where on SPSS is the Kolmogorov Smirnov test?
It is found under Analyze ---> Nonparametric Tests ---> 1 Sample K-S
How critical value is calculated in Kolmogorov-Smirnov test?
if my data followed to a special distribution, how can i calculate the critical value of k-s test in this case?
What are examples of nonparametric statistics?
Fisher's exact probability test, chi-square test for independence, Kolmogorov-Smirnov test, Spearman's Rank correlation and many, many more.
How do you determine if variances are similar?
If the two distributions can be assumed to follow Gaussian (Normal) distributions then Fisher's F-test is the most powerful test. If the data are at least ordinal, then you can use the Kolmogorov-Smirnov two-sample test.
How do you interpret a KSL or Kolmogorov-Smirnov-Lilliefors test?
If the test result is significant (Lower than or equal to 0.05) = The data is not normally distributed... If the test result is not significant (Higher than 0.05) = The data is normally distributed... This synchronize with the Statistical Hypothesis Assumption (Ho and Ha) Ho means "Nothing Happen" and Ha means "Something Happen" then for KSL and Shapiro Wilk test of normality assumption also.... If the test result reject Ha and accept Ho means "NOTHING HAPPEN" to data or the data is normally distributed but if the result reject Ho and accept Ha means "SOMETHING HAPPEN" to data or in this case the data is NOT normally distributed. Dr.Tanarat Thiengkamol (send2nude@gmail.com)
When it comes to comparing data from different distributions what is the benefit of normal standard distribution?
There may or may not be a benefit: it depends on the underlying distributions. Using the standard normal distribution, whatever the circumstances is naive and irresponsible. Also, it depends on what parameter you are testing for. For comparing whether or not two distributions are the same, tests such as the Kolmogorov-Smirnov test or the Chi-Square goodness of fit test are often better. For testing the equality of variance, an F-test may be better.
How do you interpret z-test result?
interpret it by letters...........
How do you test the normality of a random variable?
There are various goodness-of-fit tests. The chi-square and Kolmogorov-Smirnoff tests are two of the better known of these.
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What factors can make chemical test for carbohydrates difficult to interpret?
Colors. This is because they mess up light and it is hard to interpret if they actually contain what you are looking for.
