(a) Based on the regression output provided above, what relation can you infer b

Question

(a) Based on the regression output provided above, what relation can you infer between Lily Valley’s sales of the lavender rose variety soap and the price and number of retail displays of the soap?

(b) How do you interpret the sign of the coefficients for the price and number of retail price in the regression analysis? Give an economic explanation for the signs.

(c) What is the price elasticity of demand for the lavender rose variety at the current sales and pricing point?

(d) Using your answer in (c) above, can you suggest what kind of strategy (price cut or price rise) that Lily Valley should consider?  

Variable Bars of lavender soap sold Price of each bar of soap Number of retail displays Average Value 2500 $1.60 170 Suppose it carries out a regression analysis on its historical data and obtains the following output: Standard Coefficients Errort Stat P-value 7380 1348.81 5.47 -1261.21 186.77-6.75 0.81 Intercept 0.00 Price #of Displays 0.00 -6.36 7.82 0.43

Explanation / Answer

a)

The relationship equation is

Sales = 7380 – 1261.21*price - 6.36*number of retail displays.

The price of relationship between the sales and the price is very significant as p values is 0.

b)

Negative sign indicates that with increase in the variable values there will be a decrease.

For example, if the price is increased by one unit the sales will decrease by 1261.21.

c)

Price elasticity is a measure of price sensitivity expressed as the percent change in quantity demanded for a given percent change in price

For 1% change in the price the sales will decrease by 0.001709% .

d)

The Lily valley should adopt the strategy of price cut as it will increase the sales

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