How do you do a one sample Kolmogorov-Smirnov test?
Assumptions.
- From the menus choose: Analyze > Nonparametric Tests > Legacy Dialogs > 1-Sample K-S…
- Select one or more numeric test variables. Each variable produces a separate test.
- Optionally, click Options for descriptive statistics, quartiles, and control of the treatment of missing data.
When should I use the Shapiro-Wilk Test?
The Shapiro–Wilk test is more appropriate method for small sample sizes (<50 samples) although it can also be handling on larger sample size while Kolmogorov–Smirnov test is used for n ≥50. For both of the above tests, null hypothesis states that data are taken from normal distributed population.
Which is the KS statistic for K-S two sample test?
DO NOT USE “KS” showing in the output table ‘K-S Two-Sample Test (Asymptotic)’. The D statistic is the maximum difference between the cumulative distributions between events (Y=1) and non-events (Y=0). In this example, D=0.603. Higher the value of D, the better the model distinguishes between events and non-events.
When to use the KS test in Freq?
“One Sided” (comparing a data distribution to a model one, like a normal distribution) – in fact the KS test is the BEST test to determine if you sample actually is consistent with a normal distribution. The KS test can not be used on data samples with less than about 10 values since you can’t really construct a realiably cumulative freq.
Can a K-S test be used for discrete distributions?
Note that although the K-S test is typically developed in the context of continuous distributions for uncensored and ungrouped data, the test has in fact been extended to discrete distributions and to censored and grouped data. We do not discuss those cases here.
What is the importance of the KS test?
Most importantly, the KS test allows one to compare arbitrary distributions to one another. That is, the distributions do not have to be normal. This is quite important.