The Spar in Muscat mall have recently introduced scanners at the checkout counters. The scanners record data on various aspects of a product, for instance, price, number of units sold and whether any promotional activities was carried out for that product or not. In doing so, the Spar management can evaluate whether price and promotional activities (if any) have any effect on sales of a product. Promotional activities are mainly of two types viz (i) flyers distributed outside the store (Flyer) and (ii) in-store displays at the end of an isle that attract a customer’s attention to the said product (Display). Data was collected on 40 different brand of food & beverage products for the month of May 2019, including sales(Y, number of units sold), price (X1, in OMR), flyer (X2, 1 if product was promoted through flyers, 0 if not) and display (X3, 1 if a special display of the product was used, 0 if not). As a preliminary analysis, a simple linear regression model was fitted to check the effect of price on sales. Part of the R output is given below: Estimate Standard Error Intercept 22.59 13.01 Price -0.014 0.0056 RSquare = 59.7%. Express the corresponding least squares regression model. Interpret the slope coefficient Suppose Hyper City is launching a new beverage brand which is priced at OMR136. What will be the predicted sale?
The Spar in Muscat mall have recently introduced scanners at the checkout counters. The scanners record data on various aspects of a product, for instance, price, number of units sold and whether any promotional activities was carried out for that product or not. In doing so, the Spar management can evaluate whether price and promotional activities (if any) have any effect on sales of a product. Promotional activities are mainly of two types viz (i) flyers distributed outside the store (Flyer) and (ii) in-store displays at the end of an isle that attract a customer’s attention to the said product (Display).
Data was collected on 40 different brand of food & beverage products for the month of May 2019, including sales(Y, number of units sold), price (X1, in OMR), flyer (X2, 1 if product was promoted through flyers, 0 if not) and display (X3, 1 if a special display of the product was used, 0 if not). As a preliminary analysis, a simple linear regression model was fitted to check the effect of price on sales. Part of the R output is given below:
|
|
Estimate |
Standard Error |
|
Intercept |
22.59 |
13.01 |
|
Price |
-0.014 |
0.0056 |
RSquare = 59.7%.
- Express the corresponding least squares regression model.
- Interpret the slope coefficient
- Suppose Hyper City is launching a new beverage brand which is priced at OMR136. What will be the predicted sale?
- The proportion of variability in sales that is not accounted for by price is……
- True/False : The
correlation coefficient between price and sale is 0.773
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