In: Statistics and Probability
X Y
Years of Education Number of Arrests
12 5
9 9
17 0
15 0
13 2
10 6
1)
ΣX | ΣY | Σ(x-x̅)² | Σ(y-ȳ)² | Σ(x-x̅)(y-ȳ) | |
total sum | 76 | 22 | 45.33333333 | 65.3 | -51.67 |
mean | 12.67 | 3.67 | SSxx | SSyy | SSxy |
sample size , n = 6
here, x̅ = Σx / n= 12.67 ,
ȳ = Σy/n = 3.67
SSxx = Σ(x-x̅)² = 45.3333
SSxy= Σ(x-x̅)(y-ȳ) = -51.7
estimated slope , ß1 = SSxy/SSxx = -51.7
/ 45.333 = -1.1397
intercept, ß0 = y̅-ß1* x̄ =
18.1029
so, regression line is Ŷ =
18.1029 + -1.1397 *x
SSE= (SSxx * SSyy - SS²xy)/SSxx =
6.449
std error ,Se = √(SSE/(n-2)) =
1.270
correlation coefficient , r = Sxy/√(Sx.Sy)
= -0.9494
1)coefficient of determination = R² =
(Sxy)²/(Sx.Sy) = 0.9013
2)It means 90.13 % of variatiion in Y(Number of Arrests) can be explained by X(Years of Education)
3)
R = 0.65
R square = 0.4225
t means 42.25% of variatiion in Y(Number of Arrests) can be
explained by X(Years of Education)
-----------------------------------------------------------
Ho: ρ = 0
tail= 2
Ha: ρ ╪ 0
n= 6
alpha,α = 0.01
correlation , r= -0.9494
t-test statistic = r*√(n-2)/√(1-r²) =
-6.044
DF=n-2 = 4
critical t-value = 4.6041
Please revert in case of any doubt.
Please upvote. Thanks in advance