Multiple Regression Model for Assessed Value with Age and Heating Area as Independent Variables

BUSINESS RESEARCH METHODOLOGY
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A multiple regression model has been run taking into consideration assessed value as the
dependent variable while there are two independent variables in the form of age and heating
area. The requisite output obtained using Excel is indicated as follows.
The requisite regression equation is indicated as follows.
Accessed Value = 163,775.1236 + 10.7252*Heating Area -284.2543*Age
The intercept of the model is 163,777.1236 while the respective slopes of the two
independent variables are 10.7252 and -284.2543. The R2 value for the above regression
model is 0.8265 which implies that the jointly the variation in the independent variables can
offer explanation for 82.65% of the variation in the dependent variable. Hence, the given
model represents a good fit (Eriksson & Kovalainen, 2015).
In order to ascertain if there is a significant relationship between assessed value and heated
area of house, it needs to be ascertained if the above regression slope is significant or not
through the means of hypothesis testing.
The relevant hypotheses are as stated below.
Null Hypothesis: βHeatingArea = 0
Alternative Hypothesis: βHeatingArea ≠ 0
The level of significance is assumed as 5%.