Caf Kaffi is a coffee shop chain that focuses on reasonably priced coffee and

comfortable atmosphere. Caf Kaffi is considering expanding further and is

evaluating two different sites for a new coffee shop. It already owns 47 shops and

has collected data on those to help with its decision making. The data includes

information on last year's revenues (in million pounds), management and staff

quality (on a 9 point scale), type of location (1 for prime location, 0 for nonprime

location), local per capita annual income (in thousand pounds), and an index of

competitor density (in number of competitors per km2). The data is available in the

fileCafeKaffi.xlsx.

a) (15%) Build, interpret, and analyze a regression model that can be used to forecast

the revenues of a new coffee shop.

b) (10%) Two sites have been offered to Caf Kaffi. Comment on which, if either, you

would recommend that the company should go for. Base your recommendation on

the model you built in part a).

Site 1: On a pleasant street off a high street in a rural but upandcoming village.

There aren't many competitors there yet with a competition density of 0.2 (2 pubs

within 10 km2). The staff available in this area is usually loyal and hardworking.

Many commuters to a relatively closeby big city have moved to the village with

an average per capita income of 40,000. There was a coffee shop there before

that recently closed down due to the age of the owner and the site is in good

shape and does not need much work. The estimated running costs including rent

are about 60,000.

Site 2: A corner location on a high street in town that used to house a popular

hardware store. There are nine coffee shops within 10 km2. Staffing is not thought

to be a big problem but competent managers have been a hard find. The average

per capita income is 53,000. The running costs (inclusive) are thought to be about

160,000.

The data set is in an open link See comment