Distribution Fitting Software & Articles

Normal Distribution

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The Normal distribution is the most widely used distribution in statistics and many other sciences. It is a family of distributions that have the same general shape, differing in their location and scale parameters.

Parameters

- scale parameter ()
- location parameter

Domain

Probability Density Function (PDF)

Normal distribution PDF

Normal Distribution Fitting

EasyFit allows to automatically or manually fit the Normal distribution and 55 additional distributions to your data, compare the results, and select the best fitting model using the goodness of fit tests and interactive graphs. Watch the short video about EasyFit and get your free trial.

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Normal Distribution Graphs and Properties

EasyFit displays all graphs and properties of the Normal distribution, presenting the results in an easy to read & understand manner. EasyFit calculates statistical moments (mean, variance etc.), quantiles, tail probabilities depending on the distribution parameters you specify.

Random Numbers from the Normal Distribution

You can easily generate random numbers from the Normal distribution in a variety of ways:

  • directly from EasyFit
  • in Excel sheets using the worksheet functions provided by EasyFitXL
  • in your VBA applications using the EasyFitXL library

Excel Worksheet and VBA Functions

EasyFitXL enables you to use the following functions in your Excel sheets and VBA applications:

Function Name
Description
NormalPdf Probability Density Function
NormalCdf Cumulative Distribution Function
NormalHaz Hazard Function
NormalInv Inverse CDF (Quantile Function)
NormalRand Random Numbers
NormalMean Mean
NormalVar Variance
NormalStdev Standard Deviation

Learn more: EasyFit Help on the Normal distribution

Applications

Some examples of the approximately normally distributied variables are:

  • the logarithm of measures of size of living tissue (length, height, skin area, weight);
  • the measurement errors in experimental results;
  • the variation of component dimensions in manufacturing processes;
  • the logarithm of interest rates, exchange rates, and inflation;
  • the intensity of laser light.