Demand and Regression Analysis

In summary, Branded Products, Inc. has successfully introduced their new Super Detergent to the market, despite facing strong competition from major players. The regression model used to forecast sales shows that price, competitor price, advertising expenditures, disposable income per capita, and month all have a significant impact on demand. In case of a recession, the company's revenue will be affected due to a decrease in disposable income per capita. The regression model explains 91.47% of the variation in sales, indicating its reliability. Branded Products should be concerned about its main competitors, as any changes in their price will have a direct impact on the company's revenue. To maintain their market share, Branded Products may need to adjust their price to compensate
  • #1
rr2013
2
0
A bit confused with this question. my answers are below each question. please help.

Branded Products, Inc., based in Halfway Tree is a leading producer and marketer of household laundry detergent and bleach products. About a year ago, Branded products rolled out its new Super Detergent in four western parishes, following success in more limited test markets. At the time of introduction, management wondered whether the company could successfully crack this market, dominated by Breeze and other major players. The following regression model forecast results for Super Detergent over the past seven months (30 weeks). The t-statistics are in parenthesis.
Q = 867.98 – 81.86P + 0.007A + 0.006I + 82.86Px + 1.309T
(345) (24) (0.7) (0.2) (18) (0.063)
R2 = 91.47%, Standard of Error of the Estimate = 33.64 t(0.01, (n-k)df) = 2.492, F(k-1, n-k, 0.01) = 3.895
Q is the demand in cases, P is tile price (per case), Px is the competitor price, A is advertising expenditures (in thousands of dollars), I is disposable income per capita (in thousands of dollars) and T represent the month.
If P = $700.5, Px = $750 A= $350,000 I = $900,0001.What is the revenue implication for Branded Products, if there a recession? If there is a recession income will be affected(reduced) and this reduce revenue; a 302.24 reduction- (dervived from subtracting t-test values- 345-(24+.7+18+0-0.063)

2.What proportion of the variation in super detergent sales is explained by the regression model?
91.47%

3.Determine if Branded products should be concerned about its main competitors
yes any change in comptetirs price will affect barnded products revenue by 18%

4.If Branded Products wants to maintain at least its share of the market, what change in the price of their detergent will be necessary to compensate for a \$100 decrease in the price of its main competitors’ detergent?
$700-$700*18%=$574
 
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  • #2
Welcome to MHB, rr2013! :)

rr2013 said:
A bit confused with this question. my answers are below each question. please help.

Branded Products, Inc., based in Halfway Tree is a leading producer and marketer of household laundry detergent and bleach products. About a year ago, Branded products rolled out its new Super Detergent in four western parishes, following success in more limited test markets. At the time of introduction, management wondered whether the company could successfully crack this market, dominated by Breeze and other major players. The following regression model forecast results for Super Detergent over the past seven months (30 weeks). The t-statistics are in parenthesis.
Q = 867.98 – 81.86P + 0.007A + 0.006I + 82.86Px + 1.309T
(345) (24) (0.7) (0.2) (18) (0.063)
R2 = 91.47%, Standard of Error of the Estimate = 33.64 t(0.01, (n-k)df) = 2.492, F(k-1, n-k, 0.01) = 3.895
Q is the demand in cases, P is tile price (per case), Px is the competitor price, A is advertising expenditures (in thousands of dollars), I is disposable income per capita (in thousands of dollars) and T represent the month.
If P = $700.5, Px = $750 A= $350,000 I = $900,0001.What is the revenue implication for Branded Products, if there a recession? If there is a recession income will be affected(reduced) and this reduce revenue; a 302.24 reduction- (dervived from subtracting t-test values- 345-(24+.7+18+0-0.063)

I'm not sure what you're doing here.
You can't use t-values this way.
It seems to me that to predict the impact of a recession, we wouldn't assume a change in our own price, nor the competitor's price, advertising expenditures, or the month.
We would assume a change in the disposable income per capita...

2.What proportion of the variation in super detergent sales is explained by the regression model?
91.47%

Right.

3.Determine if Branded products should be concerned about its main competitors
yes any change in comptetirs price will affect barnded products revenue by 18%

How did you get that?

4.If Branded Products wants to maintain at least its share of the market, what change in the price of their detergent will be necessary to compensate for a \$100 decrease in the price of its main competitors’ detergent?
$700-$700*18%=$574

How did you get that?

Maintaining the share of the market implies there should be no change in quantity.
That does not seem to be what you are doing.
 
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  • #3
I like Serena said:
Welcome to MHB, yaoming988! :)
I'm not sure what you're doing here.
You can't use t-values this way.
It seems to me that to predict the impact of a recession, we wouldn't assume a change in our own price, nor the competitor's price, advertising expenditures, or the month.
We would assume a change in the disposable income per capita...
Right.
How did you get that?
How did you get that?

Maintaining the share of the market implies there should be no change in quantity.
That does not seem to be what you are doing.

Quote - regarding question one I subtracted the t values of all the factors excluding income - i saw something similar done in an example online but I'm not certain I'm on the right track please guide me in answering this question.

thr truth is I'm sure i should be using the values given to answer the questions i.ethe t test, f test, rsquared etc but i do not know how to go about doing that. The examples we work in class are a lot simplier.

- - - Updated - - -

rr2013 said:
Quote - regarding question one I subtracted the t values of all the factors excluding income - i saw something similar done in an example online but I'm not certain I'm on the right track please guide me in answering this question.

thr truth is I'm sure i should be using the values given to answer the questions i.ethe t test, f test, rsquared etc but i do not know how to go about doing that. The examples we work in class are a lot simplier.

can you please walk me through answering this question
 
  • #4
rr2013 said:
can you please walk me through answering this question

Can you walk us through your answers?
 
  • #5


Based on the regression model, it appears that Branded Products has been successful in cracking the western parishes market with their Super Detergent. The high R2 value of 91.47% indicates that the model explains a large proportion of the variation in sales. Additionally, the t-statistics for price and competitor price show that these variables have a significant impact on demand for Super Detergent. This means that Branded Products should be concerned about their competitors and closely monitor any changes in their prices.

To maintain their share of the market, Branded Products may need to decrease their price by $574 to compensate for a $100 decrease in their main competitors' price. This is based on the regression model's coefficient for competitor price, which indicates that a 1% decrease in competitor price results in an 18% decrease in demand for Super Detergent. However, Branded Products should also consider the impact of their own advertising and income levels on demand, as these variables also have a significant impact on sales. Overall, the regression model can provide valuable insights for Branded Products to make informed decisions about their pricing and marketing strategies.
 

FAQ: Demand and Regression Analysis

What is demand analysis?

Demand analysis is a method used to understand and measure consumer demand for a particular product or service. It involves examining the relationship between the price of a product and the quantity demanded by consumers.

What is regression analysis?

Regression analysis is a statistical technique used to identify the relationship between a dependent variable (such as quantity demanded) and one or more independent variables (such as price). It helps to determine how changes in the independent variables affect the dependent variable.

How are demand and regression analysis related?

Demand analysis and regression analysis are closely related as demand analysis often uses regression analysis to identify the relationship between price and quantity demanded. Regression analysis is also used to make predictions about demand based on changes in price.

What are some common uses of demand and regression analysis?

Demand and regression analysis are commonly used in market research to determine the optimal price for a product or service, to forecast sales, and to understand consumer behavior. They are also used in economics to study the impact of changes in price on demand and supply.

What are the limitations of demand and regression analysis?

One limitation of demand and regression analysis is that it assumes a linear relationship between price and quantity demanded, which may not always be the case. Additionally, it does not account for external factors that may affect demand, such as changes in consumer preferences or economic conditions.

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