Histogram. Draws a Histogram of the supplied sample data and reports associated statistical parameters such as
Mean, Median, Variance, Standard Deviation, Skewness and Kurtosis
Linear Regression. Performs linear regression on the supplied sample data for certain predefined fitting functions.
The most common example is a least-squares fit to a straight line y = ax +b, but other plot forms are available, i.e. exponential,
power, reciprocal, and polynomial. The resulting fit is displayed as a plot of the original data points plus the fitted line. The
line coefficients a and b are reported along with a "goodness of fit" measure. A table of the original x and y points, along with
the associated fitted points an residuals is also given.
Box Plot. The Box Plot consists of a set box diagrams, each based based on its own dataset, provided as s column of
input samples within a multi-column grid. Each box gives a pictorial summary of various statistical features of the data set such
as median, quartiles and outliers.
Probability Plot. The probablity plot can be used to assess how close a set of sample data corresponds to a given
PPCC Plot. A probability plot calculates, for a given distribution type, the location and scale parameters which best
best fit the sample data. If the distribution also has a shape parameter, this must be supplied. The PPCC plot calculates multiple
probability plots for a range of shape parameters and reports the shape parameter providing the best fit.
Statistical Distributions. Plots statistical distributions (either PDF or CDF) based on supplied distribution parameters.
Available distribution types are: Normal, Exponential, Lognormal, Weibull, Gamma, Binomial.