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Binomial Distribution Simulation by Heather Pierce

Binomial Distribution Simulation by Heather Pierce
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2019-01-27 04:31
FunctionProbability & StatisticsSlider AnimationGraphing
This example demonstrates the binomial distribution random phenomenon. The core math concepts involved are binomial distribution in probability & statistics. Construction highlights include using GeoGebra commands Sequence, Sort, Max, CountIf and objects t, n, p, t_1, p_1, n_1, list, sorted, heights, Points1, Points2, l1, h, a, b, num, text1. Suitable for high school and above students learning probability statistics and discrete mathematics.

GeoGebra Commands & Parameters

  1. Sequence(RandomBinomial[n, p], i, 1, t, 1) → list
  2. Sort(list) → sorted
  3. Sequence(CountIf[x ≟ i, sorted], i, 0, n, 1) → heights
  4. Sequence((i - 0.5, Element[heights, i + 1]), i, 0, n, 1) → Points1
  5. Sequence((i + 0.5, Element[heights, i + 1]), i, 0, n, 1) → Points2
  6. Sequence(Polygon[(i - 0.5, 0), (i + 0.5, 0), Element[Points2, i + 1], Element[Points1, i + 1]], i, 0, n - 1, 1) → l1
  7. Max(Sequence[y(Element[Points1, i]), i, 1, Length[Points1]]) → h
  8. CountIf(a ≤ x ∧ x ≤ b, sorted) → num

AI Drawing Prompt Reference

Create a graph demonstrating the binomial distribution phenomenon, featuring a probability function with sliders for parameters. Generate random binomial distribution data using sequences, sort the data, and calculate frequencies for each value. Represent the frequency distribution as a bar chart, where each bar is formed by two points, with the base on the x-axis and height corresponding to frequency, showcasing the characteristic shape of the binomial distribution.
The prompt above was compiled from the original drawing commands and is for reference only.