X | Y | XY | X² | Y² |
23 | 1050 | 24150 | 529 | 1102500 |
15 | 850 | 12750 | 225 | 722500 |
22 | 1000 | 22000 | 484 | 1000000 |
28 | 1250 | 35000 | 784 | 1562500 |
35 | 1550 | 54250 | 1225 | 2402500 |
22 | 1100 | 24200 | 484 | 1210000 |
Ʃx = | Ʃy = | Ʃxy = | Ʃx² = | Ʃy² = |
145 | 6800 | 172350 | 3731 | 8000000 |
Sample size, n = | 6 |
x̅ = Ʃx/n = 145/6 = | 24.1666667 |
y̅ = Ʃy/n = 6800/6 = | 1133.33333 |
SSxx = Ʃx² - (Ʃx)²/n = 3731 - (145)²/6 = | 226.833333 |
SSyy = Ʃy² - (Ʃy)²/n = 8000000 - (6800)²/6 = | 293333.333 |
SSxy = Ʃxy - (Ʃx)(Ʃy)/n = 172350 - (145)(6800)/6 = | 8016.66667 |
a)
Slope, a = SSxy/SSxx = 8016.66667/226.83333 = 35.341661
y-intercept, b = y̅ - a* x̅ = 1133.33333 - (35.34166)*24.16667 = 279.2432
Regression equation :
ŷ = 35.3417 x + 279.2432
b)
Predicted value of y at x = 26
ŷ = (35.3417) * 26 + 279.2432 = 1198.1264
c) Correlation coefficient, r = SSxy/√(SSxx*SSyy)
= 8016.66667/√(226.83333*293333.33333) = 0.9828
d) Plot:
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if any doubt ask me in comments.
can i get help plz asap 4. A consumer welfare agency wants to investigate the relationship...
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