a)
b)
X | Y | (x-x̅)² | (y-ȳ)² | (x-x̅)(y-ȳ) |
2860 | 4.46 | 93373.898 | 0.173 | 127.249 |
2010 | 3.08 | 296402.469 | 0.928 | 524.596 |
2791 | 4.75 | 55966.041 | 0.499 | 167.121 |
2618 | 4.09 | 4041.327 | 0.002 | 2.952 |
2212 | 4.23 | 117257.33 | 0.035 | -63.84 |
2184 | 2.91 | 137217.33 | 1.285 | 419.91 |
2344 | 2.86 | 44280.18 | 1.401 | 249.06 |
2692 | 4.69 | 18925.8980 | 0.4179 | 88.9301 |
2206 | 3.72 | 121402.469 | 0.105 | 112.742 |
2914 | 5.3 | 129291.612 | 1.579 | 451.776 |
3034 | 3.46 | 229988.755 | 0.341 | -279.864 |
4240 | 6.54 | 2841151.041 | 6.232 | 4207.909 |
1400 | 3.31 | 1332705.327 | 0.538 | 846.856 |
2257 | 3.21 | 88463.755 | 0.695 | 247.928 |
ΣX | ΣY | Σ(x-x̅)² | Σ(y-ȳ)² | Σ(x-x̅)(y-ȳ) | |
total sum | 35762 | 56.61 | 5510467.429 | 14.23 | 7103.31857 |
mean | 2554.43 | 4.04 | SSxx | SSyy | SSxy |
sample size , n = 14
here, x̅ = Σx / n= 2554.43 ,
ȳ = Σy/n = 4.04
SSxx = Σ(x-x̅)² =
5510467.4286
SSxy= Σ(x-x̅)(y-ȳ) = 7103.3
estimated slope , ß1 = SSxy/SSxx = 7103.3
/ 5510467.429 = 0.0013
intercept, ß0 = y̅-ß1* x̄ =
0.7508
so, regression line is Ŷ =
0.7508 + 0.0013 *x
c)
SSE= (SSxx * SSyy - SS²xy)/SSxx =
5.074
std error ,Se = √(SSE/(n-2)) =
0.65025
Ho: ß1= 0
H1: ß1╪ 0
n= 14
alpha = 0.05
estimated std error of slope =Se(ß1) = Se/√Sxx =
0.65025 /√ 5510467
= 0.000
t stat = estimated slope/std error =ß1 /Se(ß1) =
0.0013 / 0.0003 =
4.654
t-critical value= 2.179 [excel function:
=T.INV.2T(α,df) ]
Degree of freedom ,df = n-2= 12
p-value = 0.0006
decison : p-value<α , reject Ho
Conclusion: Reject Ho and conclude that cigarette
consumption does affect the death rate from bladder cancer at
α=0.05
d)
p-value = 0.0006
decison : p-value>α=0.01 ,do not reject
Ho
Conclusion: do not Reject Ho and conclude that cigarette
consumption does not affect the death rate from bladder cancer at
α=0.01
Cigarette Smoking and Cancer Death Rates Deaths per year per 100,000 people Cigarettes Bladder per person...
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