n= | 7.0000 | |
X̅=ΣX/n | 28.34 | |
Y̅=ΣY/n | 1.86 | |
sx=(√(Σx2-(Σx)2/n)/(n-1))= | 12.77 | |
sy=(√(Σy2-(Σy)2/n)/(n-1))= | 0.7174 | |
Cov=sxy=(ΣXY-(ΣXΣY)/n)/(n-1)= | -8.9875 | |
r=Cov/(Sx*Sy)= | -0.9812 | |
slope= β̂1 =r*Sy/Sx= | -0.0551 | |
intercept= β̂0 ='y̅-β1x̅= | 3.4199 |
a)
ΣX = | 198.400 |
ΣY= | 13.000 |
ΣX2 = | 6601.260 |
ΣY2 = | 27.231 |
ΣXY = | 314.532 |
r = | -0.981 |
b)
t=r*(√(n-2)/(1-r2))= | -11.37 |
critical t = | -3.36 |
c)
Se =√(SSE/(n-2))= | 0.15161 |
a= | 3.41986 |
b= | -0.05514 |
d)
predicted val=3.42+33*-0.055= | 1.60 |
e)
standard error of PI=s*√(1+1/n+(x0-x̅)2/Sxx)= | 0.1636 | |
for 80 % CI value of t = | 1.476 | |
margin of error E=t*std error = | 0.242 | |
lower confidence bound=xo-E = | 1.36 | |
Upper confidence bound=xo+E= | 1.84 |
f_)
t=r*(√(n-2)/(1-r2))= | -11.37 |
critical t = | -3.36 |
g)
std error of slope =se(β1) =s/√Sxx= | 0.0048 | |
for 90 % CI value of t = | 2.015 | |
margin of error E=t*std error = | 0.010 | |
lower confidence bound=xo-E = | -0.065 | |
Upper confidence bound=xo+E= | -0.045 |
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