Statistics

Maple has a statistics package built in. To activate the package use the with(stats) command:

> with(stats);

      [describe, fit, importdata, random,statevalf, statplots, transform]

Let us go ahead and describe a sample data set. Note that the data is enclosed in square brackets, [].

> sample := [52.54, 89.45, 36.98, 101.32,74.03, 58.65, 18.00, 25.45];

      sample := [52.54, 89.45, 36.98, 101.32,74.03, 58.65, 18.00, 25.45]

Now we can quickly calculate the mean, median, and standard deviations with the describe command:

> describe[mean](sample);

                                  57.05250000

> describe[median](sample);

                                  55.59500000

> describe[standarddeviation](sample);

                                  27.94432131

Maple can calculate probability distributions including normal, c-squared, student T, F, and exponential. For example, suppose you had a mean value of 76.43 with a 2.3 standard deviation:

> ex_mean := 76.43;

                                ex_mean :=76.43

> ex_sdev := 2.3;

                                 ex_sdev :=2.3

Now, you want the (normald) probability that a value is <= 73.40:

> prob := statevalf[cdf,normald[ex_mean,ex_sdev]](73.40);

                              prob :=.09385374720

Maple can fit models to data via Least Squares methods. One needs to define the data:

> Xdata := [-1.9,-1.1,0.2,2.1,3.0];

                      Xdata := [-1.9, -1.1,.2, 2.1, 3.0]

> Ydata := [-4.1,-3.0,-2.2,-0.1,0.8];

                      Ydata := [-4.1, -3.0,-2.2, -.1, .8]

Now, go ahead and fit this to a standard y=mx+b equation:

>eq_fit:=fit[leastsquare[[x,y],y=m*x+b,{m,b}]]([Xdata,Ydata]);

eq_fit := y = .9758308159 x - 2.168882175


This page Maintained by Dale H. Leschnitzer
Last Modified Monday, November 4, 1996

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