Standard Normal Curve

Standard Normal Curve
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2021-11-22 12:17
This example demonstrates the construction and properties of the standard normal distribution curve. Key math concepts include normal distribution, standard deviation, integral, and probability & statistics. Construction highlights involve using Normal for the function, Sequence and Histogram for data visualization, Point and Integral for area calculation, and CountIf for frequency statistics. Suitable for high school students and beginners in statistics learning normal distribution.

GeoGebra Commands & Parameters

  1. Normal(μ, σ, x, false) → f
  2. Sequence(RandomNormal[μ, σ], x, 1, n) → l1, {40.88328609802497, 53.69490898594891, 45.13571439672866, 41.8401491072585, 17.822790503288626, 39.288126446978005, 33.45283635913074, 45.97489666164053, 26.171615825697124, 28.18414305981161, 41.84953262793489, 16.17171880519042, 34.10037370311745, 39.61595845286573, 19.684825788598012, 10.423751471055855, 28.40098480694516, 48.733494943999915, 38.122876230840916, 16.654149454512094, 25.678753841282923, 54.052831197529414, 50.53180270292209, 48.31549149001336, 31.436236927761932, 20.346742995710258, 33.1680776708063, 45.915489562671404, 33.83220676364943, 61.11189210779224, 32.32093854044034, 13.235735262194122, 27.199994719258942, 33.80300990595734, 26.735224389125417, 22.35961346308597, 17.1184438693859, 53.96430577627234, 39.105799709208156, 19.10378224321174, 5.176172333986372, 45.12528484428944, 45.45896838131348, 39.465917928818286, 36.020103155079575, 42.834375997855844, 56.21197264106527, 38.25378555873844, 14.65873164473917, 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  3. Histogram(Sequence[μ - (10 * σ), μ + (10 * σ), w], l1, true, 1 / n) → a
  4. Point(xAxis) → A
  5. Point(xAxis) → B
  6. Integral(f, x(A), x(B)) → b
  7. CountIf(x > x(A) ∧ x < x(B), l1) → g

AI Drawing Prompt Reference

Draw a combined statistical diagram in one coordinate system: plot a normal distribution density curve defined by a given mean μ and standard deviation σ (using the standard normal formula with those parameters). Generate a set of random sample values from that same normal distribution and display them as a histogram whose binning range spans from μ−10σ to μ+10σ, aligned with the curve. Choose two points on the x-axis to act as integration limits, compute the area under the normal curve between those limits, and also count how many sampled values fall within that same interval. Show the curve, the histogram, and the interval-based area/count comparison together.
The prompt above was compiled from the original drawing commands and is for reference only.