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That’s a bunch of

That’s a bunch of. Wei. BULL!!. Bridget Matamoros Guyer High School Denton, TX. Simulations Work!. But they must be: Efficient Effective Sticky. ~One 90 minute block Get the point across clearly Engaging and concrete enough that students will remember the point. Minitab ROCKS!

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That’s a bunch of

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  1. That’s a bunch of Wei BULL!! Bridget Matamoros Guyer High School Denton, TX

  2. Simulations Work! But they must be: • Efficient • Effective • Sticky ~One 90 minute block Get the point across clearly Engaging and concrete enough that students will remember the point

  3. Minitab ROCKS! 30 seat perpetual license = $1,000

  4. 300 Numbers to sample from in each population simulated from Minitab Took quite a bit of time to cut out the population data. A student aide (or spouse) is helpful here.

  5. Groups of 3-4 students randomly selected a population identified only by a letter. • They did not know any characteristics about the population. • 2 bags of the same population per group to increase speed of sampling

  6. Students worked in pairs to take samples of size 30 and calculate sample means. After 20-30 sample means were obtained they created histograms.

  7. Then came The Big Reveal…

  8. where is the mean and is the standard deviation Descriptive Statistics: Normal Variable N Mean SE Mean StDev Minimum Q1 Median Q3 Maximum Normal 300 14.620 0.288 4.991 0.000 12.000 15.000 18.000 30.000

  9. where is the parameter for the degrees of freedom and denotes the gamma function Descriptive Statistics: Chi-Squared DF=10 Variable N Mean SE Mean StDev Minimum Q1 Median Q3 Maximum ChiSquare 300 9.887 0.253 4.378 1.000 7.000 9.000 12.000 30.000

  10. where a and b are the interval minimum and maximum Descriptive Statistics: Uniform [0, 30] Variable N Mean SE Mean StDev Minimum Q1 Median Q3 Maximum Uniform 300 14.510 0.513 8.886 0.000 7.000 14.000 22.750 30.000

  11. where is the shape parameter is the scale parameter and denotes the gamma function Descriptive Statistics: Gamma Variable N Mean SE Mean StDev Minimum Q1 Median Q3 Maximum Gamma 300 9.853 0.384 6.645 0.000 5.000 8.000 13.000 40.000

  12. where a and b are the interval minimum and maximum and c is the mode Descriptive Statistics: Triangular Variable N Mean SE Mean StDev Minimum Q1 Median Q3 MaximumTriangular 300 18.893 0.371 6.424 0.000 15.000 20.000 24.000 30.000

  13. where is the location parameter and is the scale parameter Descriptive Statistics: Laplace Variable N Mean SE Mean StDev Minimum Q1 Median Q3 Maximum Laplace 300 15.380 0.242 4.187 0.000 13.000 15.000 18.000 30.000

  14. where are the shape parameters and denotes the gamma function Descriptive Statistics: Beta*30 Variable N Mean SE Mean StDev Minimum Q1 Median Q3 Maximum Beta*30 300 15.147 0.715 12.381 0.000 1.000 16.000 28.000 30.000

  15. where is the shape parameter and is the scale parameter Descriptive Statistics: Weibull Variable N Mean SE Mean StDev Minimum Q1 Median Q3 Maximum Weibull 300 8.877 0.720 12.478 0.000 1.000 4.000 11.000 100.000

  16. Outcomes Approximately normal sampling distributions for almost all groups Only a handful were approximately normal They actually worked fairly efficiently Students to bore quickly with monotonous calculations Students internalized the CLT more effectively by comparing populations Lingering confusion about the CLT We barely finished histograms and closed up discussion the next day Activity to take only one class period

  17. Un-Expected Results • Exposure to the Nearly Normal Condition Weibull and others were SO skewed that a sample size of 30 was not sufficient to produce an approximately normal sampling distribution Populations that were unimodal and not severely skewed produced sampling distributions closer to normal • Later reinforcement of the Nearly Normal Condition I referred to the activity and in particular the Weibull distribution numerous times for T inference procedures.

  18. Improvements • Play musicduring sampling to keep energy up (student recommended) • Write a calculator program instead PRO: Faster sampling CON: Not concrete enough for some students to get the point • JIGSAW Methodmight work better

  19. Students go to different groups where they work together to create the sampling distribution. • Each member produces their own copy of the histogram. • They go back to their original groups to share/compare results before whole class discussion. • JIGSAW Method

  20. Want more bull?bmatamoros@dentonisd.org

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