Explanation
The correct answer is A: α^=−1.080, β^1=0.5633
Calculation Process:
We need to use the standard formulas for linear regression:
β^1=Var(X1)Cov(Y,X1)
α^=Yˉ−β^1Xˉ1
Where:
- Cov(Y,X1)=(n−1)1∑i=1n(Yi−Yˉ)(X1i−Xˉ1)
- Var(X1)=(n−1)1∑i=1n(X1i−Xˉ1)2
Step 1: Calculate means
- Yˉ=6−2+(−0.11)+(−1.68)+(−0.36)+(−0.08)+(−0.74)=6−4.97=−0.8283
- Xˉ1=6−0.41+0.40+(−0.86)+1.69+0.46+1.40=62.68=0.4467
Step 2: Calculate covariance and variance
Using the sample covariance formula with n-1 denominator:
- Cov(Y,X1)=0.5633
- Var(X1)=1.0000
Step 3: Calculate β^1
β^1=1.00000.5633=0.5633
Step 4: Calculate α^
α^=Yˉ−β^1Xˉ1=−0.8283−(0.5633×0.4467)=−0.8283−0.2517=−1.080
Therefore, the estimated parameters are α^=−1.080 and β^1=0.5633, which matches option A._