Geometric Interpretation of Pearson's Correlation Coefficient (Draft)

Geometric Interpretation of Pearson's Correlation Coefficient (Draft)
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2014-09-26 03:45
This example attempts to geometrically interpret Pearson's correlation coefficient. It involves core concepts of random variables and correlation. By constructing orthogonal lines, intersections, vectors, polygons, etc., it demonstrates how to calculate and understand the correlation coefficient. Suitable for high school mathematics education and learning.

GeoGebra Commands & Parameters

  1. OrthogonalLine(B, b) → c
  2. Intersect(b, c) → E
  3. Intersect(a, b) → meanxy
  4. OrthogonalLine(C, b) → e
  5. OrthogonalLine(D, b) → f
  6. OrthogonalLine(B, a) → g
  7. OrthogonalLine(A, a) → h
  8. OrthogonalLine(A, b) → i
  9. OrthogonalLine(C, a) → j
  10. OrthogonalLine(D, a) → k
  11. Intersect(b, e) → G
  12. Intersect(b, f) → H
  13. Intersect(b, i) → I
  14. Intersect(a, h) → J
  15. Intersect(a, g) → K
  16. Intersect(a, j) → L
  17. Intersect(a, k) → M
  18. Vector(E, B) → B_x
  19. Vector(I, A) → A_x
  20. Vector(G, C) → C_x
  21. Vector(H, D) → D_x
  22. Polygon(B, E, meanxy, K) → poly_B, B_1, e_1, meanxy_1, k_1
  23. Polygon(A, I, meanxy, J) → poly_A, a_1, i_1, meanxy_2, j_1
  24. Polygon(meanxy, L, C, G) → poly_C, meanxy_3, l_1, c_1, g_1
  25. Polygon(meanxy, M, D, H) → poly_D, meanxy_4, m, d_1, h_1
  26. Vector(K, B) → B_y
  27. Vector(J, A) → A_y
  28. Vector(L, C) → C_y
  29. Vector(M, D) → D_y
  30. Sum(signedareas) → Sxy
  31. Sum(x({A_x, B_x, C_x, D_x})^(2)) → Sxx
  32. Sum(y({A_y, B_y, C_y, D_y})^(2)) → Syy
  33. OrthogonalLine(F, a) → l
  34. OrthogonalLine(N, b) → n
  35. Intersect(l, n) → O
  36. Polygon(meanxy, N, O, F) → poly1, meanxy_5, n_1, o, f_1
  37. Line(P, xAxis) → p
  38. Circle(P, Segment[meanxy, J]) → q
  39. Intersect(q, p, 2) → Q
  40. Circle(Q, Segment[meanxy, K]) → r
  41. Intersect(r, p, 2) → R
  42. Circle(R, Segment[meanxy, L]) → s
  43. Intersect(s, p, 2) → S
  44. Circle(S, Segment[meanxy, F]) → t
  45. OrthogonalLine(Q, p) → b_1
  46. OrthogonalLine(R, p) → m_1
  47. OrthogonalLine(S, p) → p_1
  48. Polygon(P, Q, 4) → poly2, r_1, s_1, t_1, a_2, U, V
  49. Polygon(Q, R, 4) → poly3, b_2, c_2, d_2, e_2, W, Z
  50. Polygon(R, S, 4) → poly4, f_2, g_2, h_2, i_2, A_1, C_1
  51. Circle(S, Segment[meanxy, M]) → q_1
  52. Intersect(q_1, p, 2) → T
  53. OrthogonalLine(T, p) → j_2
  54. Polygon(S, T, 4) → poly5, k_2, l_2, m_2, n_2, D_1, E_1
  55. Circle(P, u) → p_2
  56. Intersect(p_2, p) → F_1, G_1
  57. Polygon(P, G_1, 4) → poly6, q_2, r_2, s_2, t_2, H_1, I_1
  58. OrthogonalLine(P, p) → a_3
  59. Circle(P, Segment[meanxy, I]) → c_3
  60. Intersect(c_3, a_3, 1) → J_1
  61. Circle(J_1, Segment[meanxy, E]) → d_3
  62. Intersect(d_3, a_3, 1) → K_1
  63. Circle(K_1, Segment[meanxy, G]) → e_3
  64. Intersect(e_3, a_3, 1) → L_1
  65. Circle(L_1, Segment[meanxy, H]) → f_3
  66. Intersect(f_3, a_3, 1) → M_1
  67. Polygon(J_1, P, 4) → poly7, b_3, g_3, h_3, i_3, N_1, O_1
  68. Polygon(K_1, J_1, 4) → poly8, j_3, k_3, l_3, m_3, P_1, Q_1
  69. Polygon(L_1, K_1, 4) → poly9, n_3, p_3, q_3, r_3, R_1, S_1
  70. Polygon(M_1, L_1, 4) → poly10, s_3, t_3, a_4, b_4, T_1, U_1
  71. Circle(P, v) → c_4
  72. Intersect(c_4, a_3) → V_1, W_1
  73. Polygon(V_1, P, 4) → poly11, d_4, e_4, f_4, g_4, Z_1, A_3
  74. OrthogonalLine(V_1, a_3) → h_4
  75. OrthogonalLine(G_1, h_4) → i_4
  76. Intersect(h_4, i_4) → B_3
  77. Polygon(V_1, B_3, G_1, P) → poly12, v_1, b_5, g_5, p_4
  78. OrthogonalLine(A_2, p) → j_4
  79. OrthogonalLine(B_2, p) → k_4
  80. OrthogonalLine(D_2, p) → l_4
  81. OrthogonalLine(C_2, p) → m_4
  82. Intersect(p, j_4) → E_2
  83. Intersect(p, k_4) → F_2
  84. Intersect(p, m_4) → G_2
  85. Intersect(p, l_4) → H_2
  86. Polygon(V_1, D_2, H_2, P) → poly13, v_2, d_5, h_5, p_5
  87. Mirror(V_1, a_3) → I_2
  88. Mirror(D_2, a_3) → J_2
  89. Mirror(H_2, a_3) → K_2
  90. Mirror(P, a_3) → P'
  91. Polygon(I_2, J_2, K_2, P') → poly13', i_5, j_5, k_5, p'
  92. Segment(C_2, G_2) → n_4
  93. Segment(D_2, H_2) → q_4
  94. Segment(A_2, E_2) → r_4
  95. Segment(B_2, F_2) → s_4
  96. Vector((x(P), y(P) - vecax), (x(A_2), y(P) - vecax)) → w
  97. Vector((x(A_2), y(P) - vecbx), (x(B_2), y(P) - vecbx)) → u_1
  98. Vector((x(B_2), y(P) - veccx), (x(C_2), y(P) - veccx)) → w_1
  99. Vector((x(C_2), y(P) - vecdx), (x(D_2), y(P) - vecdx)) → u_2
  100. PMCC({A, B, C, D}) → pearcorr

AI Drawing Prompt Reference

Draw a geometric figure to explain Pearson's correlation coefficient. Start by constructing two perpendicular lines b and a, then find intersection points like E and meanxy. Next, construct vectors and polygons such as B_x and A_x. Finally, calculate the components of the correlation coefficient, such as Sxx and Syy.
The prompt above was compiled from the original drawing commands and is for reference only.