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Simulation and Normal Distribution

Simulation and Normal Distribution
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2016-06-03 19:14
FunctionProbability & StatisticsTransformation
In collections Statistics Simulations Statistics Simulations
This example demonstrates how to simulate data and create a histogram to visualize the characteristics of a normal distribution. Key math concepts include Dilation, Normal Distribution, Cylinder, Arithmetic Mean, and Histogram. It utilizes GeoGebra commands and objects such as Join, Shuffle, Take, Sum, DotPlot, Segment, and variables like a, seven, eight, list1, list2, shufsev, shufeight, sumeight, sumseven, b, button1, data, list3, text1, f, g. Suitable for high school students learning probability, statistics, and data analysis.

GeoGebra Commands & Parameters

  1. Join({Sequence[1, a, 1, 676], Sequence[0, a, 1, 1009 - 676]}) → seven
  2. Join({Sequence[1, a, 1, 622], Sequence[0, a, 1, 1020 - 622]}) → eight
  3. Join({seven, eight}) → list1
  4. Shuffle(list1) → list2
  5. Take(list2, 1, 1009) → shufsev
  6. Take(list2, 1010, 2029) → shufeight
  7. Sum(shufeight) → sumeight
  8. Sum(shufsev) → sumseven
  9. DotPlot(data, false, 0.4) → list3
  10. Segment((-0.06, 3), (-0.06, 0)) → f
  11. Segment((0.06, 3), (0.06, 0)) → g