X

Y

m_O

(Y-Y_O)^2

(Y-Y_s)^2

Somma_O

Somma_s

Y_O

Y_s

Retta s di regressione
  Y = 1,81X - 0,33

Retta s_O dei minimi quadrati per O
                Y = 1,74X

A2 = 0
A3: A2 + 1
A4: A3 + 1
A5: A4 + 1
A6: A5 + 1
A7: A6 + 1
A8: A7 + 1
A9: A8 + 1
B2 = 0
B3 = 1.6
B4 = 2.8
B5 = 5.5
B6 = 6.1
B7 = 8.9
B8 = 10.3
B9 = 12.8
A: (A2, B2)
B: (A3, B3)
C: (A4, B4)
D: (A5, B5)
E: (A6, B6)
F: (A7, B7)
G: (A8, B8)
H: (A9, B9)
lista1: {A, B, C, D, E, F, G, H}
s = FitLineY(lista1)
m_O = 1.74285714285714
s_0: y = (m_O * x)
C2: (m_O * A2)
C3: (m_O * A3)
C4: (m_O * A4)
C5: (m_O * A5)
C6: (m_O * A6)
C7: (m_O * A7)
C8: (m_O * A8)
C9: (m_O * A9)
E11 = Sum(E2:E9)
F11 = Sum(F2:F9)
m_s = Slope(s)
I = Intersect(s, yAxis)
q_s: y(I)
D2: (m_s * A2) + q_s
D3: (m_s * A3) + q_s
D4: (m_s * A4) + q_s
D5: (m_s * A5) + q_s
D6: (m_s * A6) + q_s
D7: (m_s * A7) + q_s
D8: (m_s * A8) + q_s
D9: (m_s * A9) + q_s
E2: (B2 - C2)^(2)
E3: (B3 - C3)^(2)
E4: (B4 - C4)^(2)
E5: (B5 - C5)^(2)
E6: (B6 - C6)^(2)
E7: (B7 - C7)^(2)
E8: (B8 - C8)^(2)
E9: (B9 - C9)^(2)
F2: (B2 - D2)^(2)
F3: (B3 - D3)^(2)
F4: (B4 - D4)^(2)
F5: (B5 - D5)^(2)
F6: (B6 - D6)^(2)
F7: (B7 - D7)^(2)
F8: (B8 - D8)^(2)
F9: (B9 - D9)^(2)
A11: SigmaXY[lista1] / SigmaXX[lista1]