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Answer :
Finding the line that fits a set of data points the best is done using the linear regression approach. We can utilize the following procedures to apply linear regression to find an equation that would most effectively predict a fair home price depending on the square footage of the home:
Step 1 :The square footage of the house should be on the x-axis and the house's price in thousands should be on the y-axis of the graph you create in step one.
Step 2: Using the slope-intercept form (y = mx + b), where m is the slope and b is the y-intercept, determine the equation of the line of best fit.
Step 3 :Find the slope and y-intercept by substituting the comps data into the equation in step three.
Step 4: The line of best fit has the equation y = mx + b, where m is the line's slope and b is its y-intercept.
Step 5: We must use the formula m = (NΣ(xy) - (Σx)(Σy)) / (NΣ(x^2) - (Σx)^2) to determine the slope (m).
Step 6: We must apply the formula b = (y - m(x)) / N to determine the y-intercept (b).
Step 7: Using the information provided in the question, we will determine the slope and y-intercept. m = (3* (108+133+120) - (1400+1700+1500)(3)) / (3 (1400+1700+1500)(2)) = 0.09 b = (108+133+120 -0.09*(1400+1700+1500))/3 = 111.33
Therefore, y = 0.09x + 111.33 is the equation that would most accurately forecast a reasonable property price based on the home's square footage.
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