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Multiple regression analysis for San Francisco demand

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Interpret the coefficient of determination (R2) for the San Francisco demand equation.
What are expected unit sales and sales revenue in a typical market?
Qi = b0 + b1Pi + b2Pxi + b3Adi + b4Ii + uit

To illustrate use of the standard error of the estimate statistic, derive the 95 percent confidence interval for expected unit sales and total sales revenue in a typical market.

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Multiple regression analysis for San Francisco demand equation. The solution contains regression, slope, intercept, correlation, r-square, coefficient of determination, regression coefficients and 95 percent confidence interval for expected unit sales and total sales revenue in a typical market.

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Please see attached file.

A. Describe the economic meaning and statistical significance of each individual independent variable included in the San Francisco demand equation.

Variable Economic Meaning Statistical Significance
Price (P)
Competitor Price (Px)
Advertising (Ad)
Income (I)

The regression coefficients give the effect of unit change in the independent variable on the dependent variable (Demand)

Price (P) :
Economic Meaning :
For a unit increase in price the demand decreases by 19875.95363 units

Statistical Significance : Since the significance value (p value ) is less than 0.05 ,the price change have significant impact on demand

Competitor Price (Px)
Economic Meaning :
For a unit increase in Competitor Price (Px) ...

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