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拖动分布

拖动分布
几何画板及绘图内容加载中，请稍等……
2014-09-17 01:58
解析几何概率统计最值优化滑块动画函数图像
所属专题 Statistical Intuition Builders
①本范例演示拖动离散数据点如何影响分布形态；②涉及核心数学概念包括分布、均值、标准差、箱线图；③构造要点：使用Polygon, PointIn, SD, Mean, Normal, BoxPlot, Segment, Intersect, Point, OrthogonalLine, Mirror, Integral等命令和对象；④适合高中及以上学生理解数据分布动态变化，用于概率统计教学。

GeoGebra 命令及参数

  1. Polygon(P_1, Q, R, S) → poly1, p, q, r, s
  2. PointIn(poly1) → B
  3. PointIn(poly1) → C
  4. PointIn(poly1) → D
  5. PointIn(poly1) → E
  6. PointIn(poly1) → F
  7. PointIn(poly1) → G
  8. PointIn(poly1) → H
  9. PointIn(poly1) → I
  10. PointIn(poly1) → J
  11. PointIn(poly1) → K
  12. PointIn(poly1) → L
  13. PointIn(poly1) → M
  14. PointIn(poly1) → N
  15. PointIn(poly1) → O
  16. PointIn(poly1) → A
  17. SD(X) → sd
  18. Mean(X) → mean
  19. Normal(mean, sd, x) → f
  20. BoxPlot(-0.02, 0.01, X, true) → median
  21. Segment(T, U) → a
  22. Intersect(a, xAxis) → V
  23. Point(xAxis) → P
  24. OrthogonalLine(P, xAxis) → b
  25. Point(Circle[V, abs(sd)]) → SD_1
  26. Segment(V, SD_1) → c
  27. Point(Circle[V, abs((2 * sd))]) → SD_2
  28. Segment(V, SD_2) → d
  29. Point(Circle[V, abs((3 * sd))]) → SD_3
  30. Segment(V, SD_3) → e
  31. OrthogonalLine(SD_1, xAxis) → g
  32. OrthogonalLine(SD_2, xAxis) → h
  33. OrthogonalLine(SD_3, xAxis) → i
  34. Mirror(SD_1, a) → SD_n1
  35. Mirror(SD_2, a) → SD_n2
  36. Mirror(SD_3, a) → SD_n3
  37. OrthogonalLine(SD_n3, xAxis) → j
  38. OrthogonalLine(SD_n2, xAxis) → k
  39. OrthogonalLine(SD_n1, xAxis) → l
  40. Integral(f, -Infinity, x(P)) → m
  41. Intersect(f, l, (8.196150479331507, 0.025765600325250028)) → Z
  42. Intersect(f, k, (-1.1950812973259275, 0.005749082526893479)) → A_1
  43. Intersect(f, j, (-10.58631307398337, 4.7191343130873153E-4)) → B_1
  44. Intersect(f, g, (26.97861403264639, 0.025765600325250028)) → C_1
  45. Intersect(f, h, (36.369845809303825, 0.005749082526893479)) → D_1
  46. Intersect(f, i, (45.76107758596127, 4.7191343130873153E-4)) → E_1
  47. Intersect(j, t) → F_1
  48. Intersect(k, t) → G_1
  49. Intersect(l, t) → H_1
  50. Intersect(g, t) → I_1
  51. Intersect(h, t) → J_1
  52. Intersect(i, t) → K_1
  53. Intersect(b, t) → L_1
  54. Intersect(f, b, (2.3743156048055805, 0.011438284314040505)) → M_1
  55. Segment(F_1, B_1) → a_1
  56. Segment(G_1, A_1) → b_1
  57. Segment(L_1, M_1) → c_1
  58. Segment(H_1, Z) → d_1
  59. Segment(I_1, C_1) → e_1
  60. Segment(J_1, D_1) → f_1
  61. Segment(K_1, E_1) → g_1

AI 绘图提示语参考

画一个多边形，并在其内部随机生成多个点，展示这些点如何影响数据的分布形状。计算这些点的均值和标准差，用正态分布曲线表示数据分布，并绘制箱线图。在坐标轴上标示均值和标准差的位置，并画出对应的标准差线。最后，通过积分和镜像操作，完善图形的展示效果。
以上提示语为根据原始绘图命令整理而来，仅供参考。