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Interactive box plot

Interactive box plot
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2020-04-24 14:53
Probability & StatisticsGeometric ConstructionGraphing
This example demonstrates a dynamic box plot where the box size changes in response to an associated frequency distribution. Key math concepts include frequency distribution, box plot, and data statistics. Construction involves commands/objects like Point, Ray, Segment, Polygon, BarChart, Frequency, Sequence. Suitable for high school mathematics education to visually illustrate data distribution characteristics and statistical changes.

GeoGebra Commands & Parameters

  1. Point(yAxis) → B
  2. Ray(B, B_1) → s
  3. OrthogonalLine(B, s) → g_1
  4. Point(g_1) → D
  5. Ray(D, D_1) → i_1
  6. Point(i_1) → E
  7. Segment(D, E) → j_1
  8. Point(j_1) → F
  9. Ray(F, F_1) → r_1
  10. Point(r_1) → I
  11. If(x(I) < x(E), E, I) → H
  12. If(x(I) < x(E), I, H) → DataUQ
  13. Segment(F, I) → f_2
  14. Point(f_2) → G_1
  15. OrthogonalLine(H, yAxis) → p
  16. Sort(Sequence[floor(RandomUniform[x(DataMin), x(DataLQ)]), k, 1, n]) → IP1Random
  17. Sort(Sequence[floor(RandomUniform[x(DataLQ), x(DataMedian)]), k, 1, n]) → IP2Random
  18. Sort(Sequence[floor(RandomUniform[x(DataUQ), 1 + x(DataMax)]), k, 1, n]) → IP4Random
  19. Sort(Sequence[floor(RandomUniform[x(DataMedian), x(DataUQ)]), k, 1, n]) → IP3Random
  20. Join({IP1Random, IP2Random, IP3Random, IP4Random}) → DataRandomPoints
  21. BarChart(DataRandomPoints, 0.6) → BarChartRandomPoints
  22. Point(s) → C
  23. Mirror(C, B) → C'_1
  24. OrthogonalLine(C, s) → f_1
  25. OrthogonalLine(C'_1, s) → h_1
  26. Segment(F, E) → k_1
  27. OrthogonalLine(I, r_1) → s_1
  28. OrthogonalLine(F, r_1) → t_1
  29. OrthogonalLine(D, r_1) → a_2
  30. OrthogonalLine(E, r_1) → b_2
  31. Midpoint(B, C'_1) → J
  32. Midpoint(C, B) → R
  33. Segment(J, R) → c_2
  34. OrthogonalLine(J, a_2) → d_2
  35. OrthogonalLine(R, a_2) → e_2
  36. Intersect(a_2, d_2) → T
  37. Intersect(a_2, e_2) → U
  38. Intersect(f_1, t_1) → V
  39. Intersect(h_1, t_1) → W
  40. Intersect(h_1, s_1) → Z
  41. Intersect(f_1, s_1) → A_1
  42. Intersect(b_2, e_2) → C_1
  43. Intersect(b_2, d_2) → E_1
  44. OrthogonalLine(G_1, e_2) → g_2
  45. Intersect(h_1, g_2) → H_1
  46. Intersect(f_1, g_2) → I_1
  47. Segment(T, U) → h_2
  48. Segment(D, F) → i_2
  49. Segment(W, V) → j_2
  50. Segment(V, A_1) → k_2
  51. Segment(A_1, Z) → l_2
  52. Segment(Z, W) → m_2
  53. Segment(H_1, I_1) → n_2
  54. Segment(I, E) → p_2
  55. Segment(E_1, C_1) → q_2
  56. Polygon(W, V, I_1, H_1) → poly3, w, v, i_3, h_3
  57. Polygon(I_1, A_1, Z, H_1) → poly4, i_4, a_3, z, h_4
  58. Frequency(IP1Random) → Freq1
  59. Frequency(IP2Random) → Freq2
  60. Frequency(IP3Random) → Freq3
  61. Frequency(IP4Random) → Freq4
  62. Frequency(DataRandomPoints) → Freq
  63. Sequence(Sum[Sequence[Element[Freq, i], i, 1, k]], k, 1, Length[Freq]) → FreqCum
  64. BarChart(x(DataMin), x(DataMax), FreqCum) → a
  65. PolyLine(Sequence[(x(DataMin) + k, Element[FreqCum, k]), k, 1, x(DataMax)]) → b

AI Drawing Prompt Reference

Draw a dynamic box plot where the box size changes based on an associated frequency distribution. Start by plotting a vertical axis and a point, then create rays and perpendicular lines to define the box plot's position. Generate four random points near the minimum, first quartile, median, and third quartile, and use these to construct the box plot. Finally, refine the plot using reflections and intersection calculations to create a complete statistical chart.
The prompt above was compiled from the original drawing commands and is for reference only.