DocsDistribution Fitting
Analyze — Statistical Methods
Distribution Fitting
Distribution fitting checks how well a numeric column matches a known distribution family — useful for validating assumptions before running other statistical methods, or just understanding the shape of your data.
Quick Start
- 1
Select a numeric column
You'll pick which one to test in the next step.
- 2
Choose Distribution fitting
Pick the column and a distribution family to test it against — Normal, Log-normal, or Exponential.
- 3
Run and read the results
Reports a Kolmogorov–Smirnov goodness-of-fit statistic plus a normality test.
Fields
Column (numeric)The numeric column whose distribution you're fitting. Required.DistributionNormal, Log-normal, or Exponential.Good to know
- Run this before a t-test or ANOVA if you're unsure whether your data is roughly normal — those tests assume it is.
- Log-normal is a common fit for data that's always positive and right-skewed, like durations or amounts.
- Exponential is typically used for time-between-events data, like wait times or time-to-failure.