-
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
distribution type.
-
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.