Distribution Tests
Chi-Square Goodness of Fit Test
Description
Determines if the sample derives from a population with a normal distribution the mean and variance of which are calculated from the sample itself.
$ H_{0}: $ Data in sample derives from a population with a normal distribution
$ H_{1}: $ Data in sample does not derive from a population with a normal distribution
Returns
- p-value
- decision
- Chi-Sq statistic
Jarque Bera Test
Description
Uses the sample skewness and sample kurtosis to determine if the sample derives from a normal distribution of unknown mean and variance.
$ H_{0}: $ Data in sample derives from a population with a normal distribution
$ H_{1}: $ Data in sample does not derive from a population with a normal distribution
Returns
- p-value
- decision
- JB statistic
One Sample Kolmogorov Smirnov Test (KS1)
Description
Determines if the sample derives from a population with a standard normal distribution.
$ H_{0}: $ Population CDF of the sample is the same as std normal CDF
Tail | Alt. Hypothesis |
---|---|
$\scriptstyle smaller\hspace{1mm}$ | Population CDF of the sample is smaller than std normal CDF |
$\scriptstyle larger\hspace{1mm}$ | Population CDF of the sample is larger than std normal CDF |
$\scriptstyle unequal\hspace{1mm}$ | Population CDF of the sample is not same as std normal CDF |
Returns
- p-value
- decision
- KS statistic
Two Sample Kolmogorov Smirnov Test (KS2)
Description
Determine if the two samples derive from the same distribution but make no assumptions about what that distribution is.
$ H_{0}: \text{population CDF of the sample 1 is the same as population CDF of sample 2} $
Tail | Alt. Hypothesis |
---|---|
$\scriptstyle smaller\hspace{1mm}$ | Population CDF of the sample 1 is smaller than population CDF of sample 2 |
$\scriptstyle larger\hspace{1mm}$ | Population CDF of the sample 1 is larger than population CDF of sample 2 |
$\scriptstyle unequal\hspace{1mm}$ | Population CDF of the sample 1 is not same as population CDF of sample 2 |
Returns
- p-value
- decision
- KS statistic