docx, 147.35 KB
docx, 147.35 KB
zip, 3.87 KB
zip, 3.87 KB
pdf, 249.04 KB
pdf, 249.04 KB

This task uses counting, probability and discrete random variables techniques to investigate the underlying mathematics of poker machines.

Students will use simulation software written in Python to design, develop and analyse a poker machine game with a variety of winning outcomes. Counting and combinatorics are used to analyse their design to ensure that it satisfies the expected “Return to Player” requirements.

Once they have designed their game, students will modify the simulation software so that it correctly models their game. The simulation code is then run, with students recording and analysing the outcomes over a number of trials, with each trial consisting of a fixed number of games.

Through mathematical analysis, the investigation will highlight that players, will in the long run lose, and indeed the more they play, the more they will lose.

Teacher Instructions

This task consists of the following files:

  • Counting-Investigation.docx containing the task description, as given to the students
  • Simulators.zip contains the simulator code to be given to students, together with example solution code files for the teacher’s use, consisting of:
    • pokie_simulator_studentversion.py the file to be given to students
    • pokie_simulator_soln_part1.py sample solution for steps 1 and 2 of the task
    • pokie_simulator_part2_sample1.py sample solution for steps 3 and 4 of the task
    • pokie_simulator_part2_sample2.py sample solution for steps 3 and 4 of the task
    • pokie_simulator_stats samples solution for steps 1 and 2 that includes statistical analysis of the results using the Statistics package
    • pokie_simulator_bust a modified version of the code that analyses how many games need to be played before the player goes bust
  • Setup-Instructions.pdf contains instructions for setting up Python and getting the simulator working
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