Interpreting Results of Distribution Fit

Distribution Fit Report Sheet

Means Test

The Means Test table provides test statistics for whether the mean of data is equal to a specific value

Chi-Square Test for Variance

The Chi-Square Test for Variance provides test statistics for whether the variance of data is equal to a specific value

Descriptive Statistics

The Descriptive Statistics table is useful in observing basic statistics of the variables, including means and standard deviations ect


The Quantiles table reveals how the variable distributes

Parameter Estimates

In addition to choose a distribution model, we also want to estimate parameters of such model. The Parameter Estimates table answers the question. The method of maximum likelihood is used to estimate parameters.

Goodness-of-Fit Tests

The Goodness-of-Fit Tests provides statistics how well a sample of data agrees with a given distribution as it's population. You can also look at the Histogram with PDF curve overlay and Probability Plot as graphical technique to evaluate the goodness of fit

Probability (P-P) Plot

The probability plot is used to test whether a dataset follows a given distribution. It shows a graph with an observed cumulative percentage on the X axis and an expected cumulative percentage on the Y axis. If all the scatter points are close to the reference line, we can say that the dataset follows the given distribution.


Histogram graphically shows properties of your data such as skewness, behavior in the tails, presence of multi-modal behavior, and data outliers. Histogram with PDF curves overlay can be compared to the shapes of PDF curves of different distributions, helping you visually identify an underlying distribution.

Box Chart

Box chart is a graphical representation of key values from summary statistics.

Cumulative Distribution Function(CDF)

The Cumulative Distribution Function plot is useful to actually determine how well the distributions fit to data.