EasyFit allows to easily and quickly select the probability distribution which best fits to data, reducing your analysis times by 70-95% over manual methods. It includes numerous features designed to save you time, prevent analysis errors, and help you make better decisions.
An integrated environment provided by EasyFit includes data management, analysis, and reporting capabilities ensuring the high quality of your projects. It is very easy to learn and use - requires only a basic knowledge of statistics, so you can master it in a day or two.
The key feature of EasyFit is the ability to automatically fit over 40 distributions to sample data. Advanced users can also apply the flexible manual fitting capability. After the distributions are fitted, they are ranked accordingly to the goodness of fit tests (Kolmogorov-Smirnov, Anderson-Darling, Chi-Squared) allowing you to select the best model.
A variety of high-quality graphs (probability density, cumulative probability, survival, hazard, P-P plot etc.) can be used to visually compare the fitted distributions and make sure you have chosen the most valid one. Finally, you can apply the integrated StatAssist tool to get a comprehensive information (moments, quantiles, probabilities) on the selected distribution.
* support for over 55 continuous & discrete distributions
* automated & manual distribution fitting
* advanced Excel integration new!
* interactive graphs
* goodness of fit tests
* distribution viewer & probability calculator
* descriptive statistics calculation
* random number generation
* Excel-like spreadsheet
* data import (Excel, ASCII)
* easy to use interface
* built-in and online help
EasyFit supports all the commonly used continuous distributions. Some of them have alternative names (indicated in parentheses):
* Burr (Burr Type 12, or Singh-Maddala)
* Cauchy (Lorentz)
* Dagum (Burr Type 3, or Inverse Burr)
* Error (Exponential Power, or Generalized Error)
* Error Function
* F Distribution
* Fatigue Life (Birnbaum-Saunders)
* Frechet (Maximum Extreme Value Type 2)
* Generalized Gamma
* Gumbel Max (Maximum Extreme Value Type 1)
* Gumbel Min (Minimum Extreme Value Type 1)
* Hyperbolic Secant
* Inverse Gaussian
* Johnson SB
* Johnson SU
* Laplace (Double Exponential)
* Log-Logistic (Fisk)
* Nakagami (Nakagami-m)
* Normal (Gaussian)
* Pareto - first kind
* Pareto - second kind (Lomax)
* Pearson Type 5 (Inverse Gamma)
* Pearson Type 6 (Beta dist. of the second kind)
* Power Function
* Rice (Ricean, or Nakagami-n)
* Student's t
Limitations in downloadable version:
Limited number of distributions.