X | Y | XY | X² | Y² |
22 | 9.6 | 211.2 | 484 | 92.16 |
27 | 9.6 | 259.2 | 729 | 92.16 |
32 | 10.1 | 323.2 | 1024 | 102.01 |
48 | 11.1 | 532.8 | 2304 | 123.21 |
65 | 13.5 | 877.5 | 4225 | 182.25 |
85 | 17.7 | 1504.5 | 7225 | 313.29 |
120 | 23.5 | 2820 | 14400 | 552.25 |
Ʃx = | 399 |
Ʃy = | 95.1 |
Ʃxy = | 6528.4 |
Ʃx² = | 30391 |
Ʃy² = | 1457.33 |
Sample size, n = | 7 |
x̅ = Ʃx/n = 399/7 = | 57 |
y̅ = Ʃy/n = 95.1/7 = | 13.58571429 |
SSxx = Ʃx² - (Ʃx)²/n = 30391 - (399)²/7 = | 7648 |
SSyy = Ʃy² - (Ʃy)²/n = 1457.33 - (95.1)²/7 = | 165.3285714 |
SSxy = Ʃxy - (Ʃx)(Ʃy)/n = 6528.4 - (399)(95.1)/7 = | 1107.7 |
Slope, b = SSxy/SSxx = 1107.7/7648 = 0.14
y-intercept, a = y̅ -b* x̅ = 13.58571 - (0.14)*57 = 5.33
Regression equation :
ŷ = 5.33 + (0.14) x
Predicted value of y at x = 47.5
ŷ = 5.33 + (0.14) * 47.5 = 11.98
Sum of Square error, SSE = SSyy -SSxy²/SSxx = 165.32857 - (1107.7)²/7648 = 4.89456
Standard error, se = √(SSE/(n-2)) = √(4.89456/(7-2)) = 0.9894
a)
Critical value, t_c = T.INV.2T(0.05, 5) = 2.5706
95% Confidence interval :
Lower limit = ŷ - tc*se*√((1/n) + ((x-x̅)²/(SSxx)))
= 11.98 - 2.5706*0.9894*√((1/7) + ((47.5 - 57)²/(7648))) = 10.98
Upper limit = ŷ + tc*se*√((1/n) + ((x-x̅)²/(SSxx)))
= 11.98 + 2.5706*0.9894*√((1/7) + ((47.5 - 57)²/(7648))) = 12.98
b)
95% Prediction interval :
Lower limit = ŷ - tc*se*√(1 + (1/n) + ((x-x̅)²/(SSxx)))
= 11.98 - 2.5706*0.9894*√(1 + (1/7) + ((47.5 - 57)²/(7648))) = 9.25
Upper limit = ŷ + tc*se*√(1 + (1/n) + ((x-x̅)²/(SSxx)))
= 11.98 + 2.5706*0.9894*√(1 + (1/7) + ((47.5 - 57)²/(7648))) = 14.71
c)
d)
Any deductions exceeding the upper limit of $ 1471 could suggest an audit.
please help The data below give the dusted gross income and the amount of Bemized deductions...
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