Estimate the frequency and cumulative distribution functions using your sample data.
Histograms, Kernel Density Function and Empirical Distribution Function are examples of common tools, available in NumXL, used in practice to estimate the shape of the statistical distribution of a data set.
Using your data in Excel, and few mouse clicks, NumXL gives you a very quick idea or view of the distribution using non-parametric methods: Histogram, KDE and EDF. Furthermore, NumXL overlays the estimated distribution with a well-known parameteric distribution (e.g. Gaussian) in the same plot.
Empirical Distribution Examples
Empirical Distribution Function
Calculates the histogram or cumulative histogram function for a given bin.
In statistics, a Q-Q Plot (“Q” stands for Quantile) creates a graphical comparison between two distribu...
In this tutorial, we’ll carry on the problem of probability density function inference, but using another...
In an earlier entry, we discussed the histogram as a non-parametric method for the probability distribution...