# Use the Kolmogorov/Lilliefors test¶

In this example we are going to perform a Kolmogorov or a Lilliefors goodness-of-fit test for a 1-d continuous distribution.

```import openturns as ot

ot.Log.Show(ot.Log.NONE)
```

Create the data.

```distribution = ot.Normal()
sample = distribution.getSample(50)
```

## Case 1 : the distribution parameters are known.¶

In the case where the parameters of the distribution are known, we must use the Kolmogorov static method and the distribution to be tested.

```result = ot.FittingTest.Kolmogorov(sample, distribution, 0.01)
print("Conclusion=", result.getBinaryQualityMeasure(), "P-value=", result.getPValue())
```
```Conclusion= True P-value= 0.9861140480396968
```

Test succeeded ?

```result.getBinaryQualityMeasure()
```
```True
```

P-Value associated to the risk

```result.getPValue()
```
```0.9861140480396968
```

Threshold associated to the test.

```result.getThreshold()
```
```0.01
```

Observed value of the statistic.

```result.getStatistic()
```
```0.06127263683768702
```

## Case 2 : the distribution parameters are estimated from the sample.¶

In the case where the parameters of the distribution are estimated from the sample, we must use the Lilliefors static method and the distribution factory to be tested.

```ot.ResourceMap.SetAsUnsignedInteger("FittingTest-LillieforsMaximumSamplingSize", 1000)
```
```distributionFactory = ot.NormalFactory()
```
```dist, result = ot.FittingTest.Lilliefors(sample, distributionFactory, 0.01)
print("Conclusion=", result.getBinaryQualityMeasure(), "P-value=", result.getPValue())
```
```Conclusion= True P-value= 0.983
```
```dist
```
Normal
• name=Normal
• dimension=1
• weight=1
• range=]-inf (-7.33957), (7.29505) +inf[
• description=[X0]
• isParallel=true
• isCopula=false

Test succeeded ?

```result.getBinaryQualityMeasure()
```
```True
```

P-Value associated to the risk

```result.getPValue()
```
```0.983
```

Threshold associated to the test.

```result.getThreshold()
```
```0.01
```

Observed value of the statistic.

```result.getStatistic()
```
```0.05110645729712043
```

Reset default settings

```ot.ResourceMap.Reload()
```