# How do you do a Kolmogorov Smirnov test in SPSS?

## How do you do a Kolmogorov Smirnov test in SPSS?

In order to test for normality with Kolmogorov-Smirnov test or Shapiro-Wilk test you select analyze, Descriptive Statistics and Explore. After select the dependent variable you go to graph and select normality plot with test (continue and OK).

How do you find the distribution of data in SPSS?

Frequency Distribution in SPSS

1. Click on Analyze -> Descriptive Statistics -> Frequencies.
2. Move the variable of interest into the right-hand column.
3. Click on the Chart button, select Histograms, and the press the Continue button.
4. Click OK to generate a frequency distribution table.

How do I make my data normally distributed in SPSS?

Quick Steps

1. Click Analyze -> Descriptive Statistics -> Explore…
2. Move the variable of interest from the left box into the Dependent List box on the right.
3. Click the Plots button, and tick the Normality plots with tests option.
4. Click Continue, and then click OK.

### Does Kolmogorov-Smirnov test for normality?

The Kolmogorov-Smirnov test is used to test the null hypothesis that a set of data comes from a Normal distribution. The Kolmogorov Smirnov test produces test statistics that are used (along with a degrees of freedom parameter) to test for normality.

How do you find the distribution of data?

Using Probability Plots to Identify the Distribution of Your Data. Probability plots might be the best way to determine whether your data follow a particular distribution. If your data follow the straight line on the graph, the distribution fits your data.

How do you find the distribution of a variable?

For quick and visual identification of a normal distribution, use a QQ plot if you have only one variable to look at and a Box Plot if you have many. Use a histogram if you need to present your results to a non-statistical public. As a statistical test to confirm your hypothesis, use the Shapiro Wilk test.

## Should I use Shapiro Wilk or Kolmogorov Smirnov?

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.