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Step Through Ryan-Joiner Test

Step Through Ryan-Joiner Test
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2013-11-22 02:07
Probability & StatisticsGeometric ConstructionSlider AnimationGraphing
In collections Statistics Step Through Applets
This example demonstrates the steps of the Ryan-Joiner test in statistics, showcasing its application through various examples. Key math concepts include statistical testing, probability distributions, expected value, and conditional probability. GeoGebra commands like Element, Sequence, Max, Min, KeepIf, TableText, Sort, CountIf, Segment, If, Polygon are used for data visualization and dynamic demonstrations. Suitable for high school students, university-level learners, and researchers in mathematics and statistics studying statistical methods and GeoGebra applications.

GeoGebra Commands & Parameters

  1. Element(RateList, Mod[Seed, 8] + 1) → Rate
  2. Sequence(Mod[Rate * k + Start, 20] + 1, k, 0, 19, 1) → OptSeq
  3. Element(DataSets, DataSet) → DataSet1
  4. Sequence(Element[DataSet1, Element[OptSeq, k]], k, 1, Size) → DataSet2
  5. Max(DataSet2) → DataMax
  6. Min(DataSet2) → DataMin
  7. Sequence(8.5 - 1.1 * k, k, 0, 2) → LHSeq
  8. Sequence(k, k, 1, 19) → StartSeq
  9. KeepIf(floor(20 / x) ≠ 20 / x, StartSeq) → RelPrime
  10. Sequence(Element[DataSet2, k], k, RL1 + 1, Size) → Data2
  11. Sequence(Element[DataSet2, k], k, 1, RL1) → Data1
  12. TableText({Data1, Data2, "hr"}) → DataList
  13. Element(DescSeq, DataSet) → DataDesc
  14. TableText({DataSet2}, "hr") → DataLine
  15. Sort(DataSet2) → SortData
  16. CountIf(x > 0, RateList) → RateNo
  17. Segment(TabL1, TabR1) → HL1
  18. Segment(TabL2, TabR2) → HL2
  19. Segment(TabL0, TabR0) → HL0
  20. CountIf(x ≠ (0, 0), DataSet1) → DataCnt
  21. If(Mod[Size, 2] ≟ 1, Segment[TabR1, TabR0], Segment[TabR2, TabR0]) → DataRight
  22. Sort(DataSet2) → DataSet3
  23. Sequence(Element[DataSet3, k], k, 1, RL1) → Data3
  24. Sequence(Element[DataSet3, k], k, RL1 + 1, Size) → Data4
  25. Sequence(k, k, 1, Size) → Index
  26. Sequence((k - 0.375) / (Size + 0.25), k, 1, Size) → PPV
  27. Sequence(InverseNormal[0, 1, Element[PPV, k]], k, 1, Size) → InvNorm
  28. Sequence(k, k, 12, 18, 1) → SizeSeq
  29. Sequence(" ", k, 1, 7) → SpSeq
  30. Element(CritSeq, Size - 11) → CritVal
  31. Polygon((HL, HT), (HR, HT), (HR, HB), (HL, HB)) → Hilite, a, b, c, d
  32. Sequence(Segment[(TL + ClWd * k, LH0), (TL + ClWd * k, LH2)], k, 0, floor(Size / 2)) → TabLines
  33. Sequence(Text[Element[Data1, k], (TL - 3.5 + k * ClWd, TT - 1.25)], k, 1, RL1) → DataRow1
  34. Sequence(Text[Element[Data2, k], (TL - 3.5 + k * ClWd, TT - 1.3 - ClHt)], k, 1, RL2) → DataRow2
  35. Sequence(Text[Element[PPV, k], (8, -7 - 1.8 * k)], k, 1, Size) → PPTxt
  36. Sequence(Text[Element[Index, k], (1.3, -7 - 1.8 * k)], k, 1, Size) → IndexTxt
  37. Sequence(Text[Element[DataSet3, k], (27, -7 - 1.8 * k)], k, 1, Size) → ODTxt
  38. Sequence(Text[Element[InvNorm, k], (17, -7 - 1.8 * k)], k, 1, Size) → InvNormTxt
  39. Sequence(Text[Element[SizeSeq, k], (38, -19 - 1.8 * k)], k, 1, 7) → SizeTxt
  40. Sequence(Text[Element[CritSeq, k], (44, -19 - 1.8 * k)], k, 1, 7) → CVSeq

AI Drawing Prompt Reference

Illustrate the steps of the Ryan-Joiner test in statistics, showcasing probability distributions, expected value, and conditional probability. Use sliders to control datasets and distributions, visualizing data with bar charts and line graphs, and label key values and statistics. First, plot the datasets and distribution curves, then add sliders to adjust parameters, finally marking the maximum, minimum, and test critical values.
The prompt above was compiled from the original drawing commands and is for reference only.