The following is the estimation results for a multiple linear regression model: Y = B. + ,X,+B, X, +E
SUMMARY OUTPUT
Regression Statistics
R-Square 0.558
Regression Standard Error (S) 863.100
Observations 35
Coeff StdError t-stat
Intercept 1283.000 352.000 3.65
X1 25.228 8.631
X2 0.861 0.372
Questions:
1. Write the fitted regression equation (30 points).
2. Write the estimated intercepts and slopes, associated with their corresponding standard errors (30 points).
3. Interpret each coefficient (40 points).

Kindly check explanation

Step-by-step explanation:

Given the summary output :

Coeff___ StdError__ t-stat

Intercept 1283.000_ 352.000 _ 3.65

X1 25.228 8.631

X2 0.861 0.372

General form of a multiple regression model:

Y = B1X1+B2X2 +E

The fitted regression equation is :

y = 25.228X1 + 0.861X2 + 1283

Intercept and slope corresponding to the standard error :

Intercept = 352

Slope 1 = 8.61 ; slope 2 = 0.372

'B' coefficient represents the change in the mean response, Y, per unit increase in a version predictor variable when all the other predictors are held constant.

B1 represents the change in the mean response, U, per unit increase in x1 when x2, x3, ..., xk are held constant

B2 represents the change in the mean response, U, per unit increase in x2 when x1, x3, ..., xk are held constant

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