It is found under Analyze ---> Nonparametric Tests ---> 1 Sample K-S
A classic would be the Kolmogorov-Smirnov test.
The Kolmogorov-Smirnov one sample test.
if my data followed to a special distribution, how can i calculate the critical value of k-s test in this case?
Fisher's exact probability test, chi-square test for independence, Kolmogorov-Smirnov test, Spearman's Rank correlation and many, many more.
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.
There are a number of statistical tests that are designed for this purpose. The Chi-squared and Kolmogorov-Smirnov tests are two of the better known ways.
You can test data using T-Test in SPSS. Click Analyze > Compare Means > Independent-Samples T-Test to run an Independent Samples T-Test in SPSS. In the Independent-Samples T-Test window, you specify the variables to be analyzed. On the left side of the screen, you will see a list of all variables in your dataset.
Boris Kolmogorov was born on 1990-01-12.
Andrey Kolmogorov was born on 1903-04-25.
Andrey Kolmogorov died on 1987-10-20.
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.
Andrey Nikolayevich Kolmogorov was born on April 25, 1903.