In: Statistics and Probability
The regression line, standard error, and Sxx for the data set are given below. The predictor value is x=2. Use the information to do parts (a) through (d).
Y(hat)=2.00+0.00x
Se=2.64575
Sxx= 5
x values: 3,4,1,2
y values: 2,3,4,-1
Part A) Determine a point estimate for the conditional mean of the response variable corresponding to the specified value of the predictor variable.
Part B) Find a 90% confidence interval for the response variable corresponding to the specified value of the predictor variable.
Part C) Determine the predicted value of the response variable corresponding to the specified value of the predictor variable.
Part D) Find a 90% prediction interval for the value of the response variable corresponding to the specified value of the predictor variable.
a)
Predicted Y at X= 2 is
Ŷ = 2.000 + 0.000
* 2 = 2.000
b)
X Value= 2
Confidence Level= 90%
Sample Size , n= 4
Degrees of Freedom,df=n-2 = 2
critical t Value=tα/2 = 2.920 [excel
function: =t.inv.2t(α/2,df) ]
X̅ = 2.50
Σ(x-x̅)² =Sxx 5.0
Standard Error of the Estimate,Se= 2.646
Predicted Y at X= 2 is
Ŷ = 2.000 + 0.000
* 2 = 2.000
standard error, S(ŷ)=Se*√(1/n+(X-X̅)²/Sxx) =
1.449
margin of error,E=t*Std error=t* S(ŷ) =
2.9200 * 1.4491 =
4.2315
Confidence Lower Limit=Ŷ +E = 2.000
- 4.2315 = -2.23
Confidence Upper Limit=Ŷ +E = 2.000
+ 4.2315 = 6.23
c)
Predicted Y at X= 2 is
Ŷ = 2.000 + 0.000
* 2 = 2.000
d)
For Individual Response Y
standard error, S(ŷ)=Se*√(1+1/n+(X-X̅)²/Sxx) =
3.0166
margin of error,E=t*std error=t*S(ŷ)=
2.9200 * 3.02 =
8.8085
Prediction Interval Lower Limit=Ŷ -E =
2.000 - 8.81 =
-6.8085
Prediction Interval Upper Limit=Ŷ +E =
2.000 + 8.81 =
10.8085