Please see two attached files: case study is the word doc; and the data is in excel.

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Babies R'Us Case Study

You have been hired as a strategic consultant by the hugely successful retailer "Babies R'Us". The company sells many products, although one product in particular, a highly innovative car seat, is being test marketed in various domestic and international markets. "Babies R'Us" has hired you to help them better understand the test market data they have compiled from 400 retailers worldwide (found in the excel file called "CarSeats.xls"). The variables in the data set include:

Unit Sales = the number of units sold (in thousands),

Competitor's Price = the price for a similar product being sold by a competitor (in dollars),

Income Level = average household income in the region (in thousands of dollars),

Advertising = amount spent on advertising the product (in thousands of dollars),

Price = the price being charged by your company (in dollars),

Population = number of people (in thousands) living in the region,

Average Age = average age of the population in the region (in years),

Average Education = average educational level in region,

Shelving location = quality of the shelf location for your product (good, medium, or bad), Urban or Rural = description of the region as urban or rural, and finally,

US = a categorical variable indicating whether the sales region is in the US or an international market.

Babies RâUs Case Study

You have been hired as a strategic consultant by the hugely successful

retailer âBabies RâUsâ. The company sells many products, although

one product in particular, a highly innovative car seat, is being test

marketed in various domestic and international markets. âBabies

RâUsâ has hired you to help them better understand the test market

data they have compiled from 400 retailers worldwide (found in the excel

file called âCarSeats.xlsâ). The variables in the data set include:

Unit Sales = the number of units sold (in thousands), Competitorâs

Price = the price for a similar product being sold by a competitor (in

dollars), Income Level = average household income in the region (in

thousands of dollars), Advertising = amount spent on advertising the

product (in thousands of dollars), Price = the price being charged by

your company (in dollars), Population = number of people (in thousands)

living in the region, Average Age = average age of the population in the

region (in years), Average Education = average educational level in

region, Shelving location = quality of the shelf location for your

product (good, medium, or bad), Urban or Rural = description of the

region as urban or rural, and finally, US = a categorical variable

indicating whether the sales region is in the US or an international

market.

Run a multiple regression model with Unit Sales as the dependent

variable against all of the available predictor variables, and use that

model to answer the questions below. NOTE: DONâT TRY TO ADD OR

DEPETE ANY OTHER VARIABLES JUST YET, SIMPLY USE ALL VARIABLES AVAILABLE

IN THE ORIGINAL DATA SET:

Which independent variables appear to be important predictors of sales?

Why?

Which are not? Any surprises? Explain!

Do you think collinearity is a problem for this data set? Explain!

Are there outliers? Which one(s)?

If this was your final model, what sort of âregionsâ should be

targeted in the future? Explain!

If it costs $80 to produce each car seat, and advertising dollars spent

represents the only additional variable cost associated with producing

this product, what would be the effect of increasing the price you

charge for each seat at retail, by $10? Explain!

Some of the international managers feel that the product is not viewed

favorably outside the US, what should you tell those managers? Explain!

Babies RâUs can usually negotiate free shelving space (due to their

volumes) if they can accept a âbadâ location. Should they do this?

Explain!

Is there evidence that advertising dollars are being well spent for this

product? Explain!

Now, determine, your own âBEST POSSIBLE MODELâ for predicting sales

(NOTE: This final model might involve new terms that you create based

upon a careful reflection of the possible need for higher order terms,

interaction terms, indicator variables, etcâ¦). Once you have found

what you consider to be the âBESTâ model, go back and modify your

answers to the above questions, IF NECESSARY!

-----------------------------

Babies R'Us Case Study

You have been hired as a strategic consultant by the hugely successful retailer "Babies R'Us". The company sells many products, although one product in particular, a highly innovative car seat, is being test marketed in various domestic and international markets. "Babies R'Us" has hired you to help them better understand the test market data they have compiled from 400 retailers worldwide (found in the excel file called "CarSeats.xls"). The variables in the data set include:

Unit Sales = the number of units sold (in thousands),

Competitor's Price = the price for a similar product being sold by a competitor (in dollars),

Income Level = average household income in the region (in thousands of dollars),

Advertising = amount spent on advertising the product (in thousands of dollars),

Price = the price being charged by your company (in dollars),

Population = number of people (in thousands) living in the region,

Average Age = average age of the population in the region (in years),

Average Education = average educational level in region,

Shelving location = quality of the shelf location for your product (good, medium, or bad), Urban or Rural = description of the region as urban or rural, and finally,

US = a categorical variable indicating whether the sales region is in the US or an international market.

Babies RâUs Case Study

You have been hired as a strategic consultant by the hugely successful

retailer âBabies RâUsâ. The company sells many products, although

one product in particular, a highly innovative car seat, is being test

marketed in various domestic and international markets. âBabies

RâUsâ has hired you to help them better understand the test market

data they have compiled from 400 retailers worldwide (found in the excel

file called âCarSeats.xlsâ). The variables in the data set include:

Unit Sales = the number of units sold (in thousands), Competitorâs

Price = the price for a similar product being sold by a competitor (in

dollars), Income Level = average household income in the region (in

thousands of dollars), Advertising = amount spent on advertising the

product (in thousands of dollars), Price = the price being charged by

your company (in dollars), Population = number of people (in thousands)

living in the region, Average Age = average age of the population in the

region (in years), Average Education = average educational level in

region, Shelving location = quality of the shelf location for your

product (good, medium, or bad), Urban or Rural = description of the

region as urban or rural, and finally, US = a categorical variable

indicating whether the sales region is in the US or an international

market.

Run a multiple regression model with Unit Sales as the dependent

variable against all of the available predictor variables, and use that

model to answer the questions below. NOTE: DONâT TRY TO ADD OR

DEPETE ANY OTHER VARIABLES JUST YET, SIMPLY USE ALL VARIABLES AVAILABLE

IN THE ORIGINAL DATA SET:

Which independent variables appear to be important predictors of sales?

Why?

Which are not? Any surprises? Explain!

Do you think collinearity is a problem for this data set? Explain!

Are there outliers? Which one(s)?

If this was your final model, what sort of âregionsâ should be

targeted in the future? Explain!

If it costs $80 to produce each car seat, and advertising dollars spent

represents the only additional variable cost associated with producing

this product, what would be the effect of increasing the price you

charge for each seat at retail, by $10? Explain!

Some of the international managers feel that the product is not viewed

favorably outside the US, what should you tell those managers? Explain!

Babies RâUs can usually negotiate free shelving space (due to their

volumes) if they can accept a âbadâ location. Should they do this?

Explain!

Is there evidence that advertising dollars are being well spent for this

product? Explain!

Now, determine, your own âBEST POSSIBLE MODELâ for predicting sales

(NOTE: This final model might involve new terms that you create based

upon a careful reflection of the possible need for higher order terms,

interaction terms, indicator variables, etcâ¦). Once you have found

what you consider to be the âBESTâ model, go back and modify your

answers to the above questions, IF NECESSARY!

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