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Interpret the final result and Draw conclusions and recommendations for the following information using the below linear regression analysis information: a =2238.383423, b = -215.6952394,

Interpret the final result and Draw conclusions and recommendations for the following information using the below linear regression analysis information:

a =2238.383423, b = -215.6952394, c = -115.7793199, and d = 0.041157311.

The approximate regression equation will be:

QD =2238.383423-215.6952394* P-115.7793199 *R +0.041157311* M

 Explanation:

The demand Equation is given by:

Demand equation: QD = a + b P + c PR + d M

Where QD is the quantity demanded for this good, P is the price per unit, PR is the price of the related good(s) in consumption (substitute or complement) and M is consumer income.

The results obtained from multiple linear Regression model is:

Regression Statistics
Multiple R 0.980212113
R Square 0.960815786
Adjusted R Square 0.95611368
Standard Error 104.7293523
Observations 29

The R-square and the adjusted R-square value is 0.960815786 and 0.95611368. This signifies that the regression model has fitted the data.

ANOVA
df SS MS F Significance F
Regression 3 6723661.421 2241220.474 204.3373447 1.04584E-17
Residual 25 274205.931 10968.23724
Total 28 6997867.352

From the ANOVA Table, it can be observed that the F-score is 204.3373447.

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 2238.383423 222.7644461 10.0482077 2.90956E-10 1779.591458 2697.175 1779.59146 2697.175388
Price of American Cheese (P) -215.6952394 112.8682107 -1.911036227 0.067531187 -448.1516706 16.76119 -448.151671 16.7611918
Price of ham (PR) -115.7793199 43.3386963 -2.671499833 0.013092455 -205.0370358 -26.5216 -205.037036 -26.52160409
Average Income (M) 0.041157311 0.00400409 10.27881639 1.83539E-10 0.032910732 0.049404 0.03291073 0.04940389

From the above table, it can be observed that the values of a =2238.383423, b = -215.6952394, c = -115.7793199, and d = 0.041157311.

Therefore, the approximate regression equation will be:

QD =2238.383423-215.6952394* P-115.7793199 *R +0.041157311* M

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