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Statistics Education


Math Apps

Student Random Variables Palette

Statistical Reference Tables

Additional Improvements

Math Apps

Binomial Distribution

Box Plots

Chi-Square Distribution

Chi-Square Tests

Confidence Intervals

Exponential Distribution

Geometric Distribution


Hypergeometric Distribution

Measures of Spread

Normal Approximation of Binomial Distribution

Poisson Distribution

Rolling Two Dice

Stem-and-Leaf Displays

Student's t-Test



Z-Test (Gradeable)





Student Random Variables Palette

A new Student Random Variables Palette contains buttons for constructing random variables based on distributions in the Student Statistics package.


Each entry is a template. To fill in the content, navigate through the placeholders by pressing Tab.


By default, the student random variables palette will not be visible on start-up in the left pane of the Maple window. To enable the palette, go to the View menu, and select Palettes>Show Palette>Student Random Variables.


For more information on palettes, see Overview of Palettes.

Student Random Variables Palette

Statistical Reference Tables

In Maple 2015, there are two new commands for generating statistical reference tables, ProbabilityTable and CriticalTable. These commands are also featured in two new reference tutors under Tools>Tutors>Statistics menu. Both of these commands also include an output option that utilizes the advances in programmatic content generation to generate embedded datatables.


The ProbabilityTable command returns a matrix of values corresponding to values in a probability distribution table. The most commonly referenced probability table is the standard normal distribution table:


ProbabilityTableNormal,x=seq0.0..1.0,0.1, output=embed:

Critical value tables are useful in hypothesis testing to determine cut-off values for various computed test statistics.

CriticalTableStudentT, output=embed:

Additional Improvements

The existing Test Guide tutor has been enhanced to accept one or two samples of data as arguments. This means that any chosen hypothesis test can be applied directly to existing data with no need to enter it into the tutor.


Chi-Square Test for Independence -------------------------------- Null Hypothesis: Two attributes within a population are independent of one another Alt. Hypothesis: Two attributes within a population are not independent of one another Dimensions: 2 Total Elements: 118 Distribution: ChiSquare(3) Computed statistic: 1.55778 Computed pvalue: 0.669002 Critical value: 7.81472828803626 Result: [Accepted] This statistical test does not provide enough evidence to conclude that the null hypothesis is false