Question

Each of the following scenarios would be described with a regression analysis. State the response variable, The explanatory variable (S), if any. Be sure to state units were appropriate.

1. We would like to explain the annual salary over employees (in thousands of dollars) which data showing their years of experience and education level (high school, college, or graduate degree).
2. We own a pizza franchise and have data regarding a city’s median income (in dollars), average number of individuals for household, number of times per week members of the household eat in restaurants, preference of toppings (cheese, sausage, pepperoni, or vegetables), and price per pizza. We would like to use this data to describe how many pizzas we might sell per week in a given city.
3. We own a shipping company and would like to estimate how much we should charge our customers to ship a package. We have data for the number of commercial clients in an area, the number of residential clients in the same area, our average number of employees, the average amount charged by our top competitor, and the average number of packages we ship per month.

Answer 1

A. Response variable: annual salary (in thousands of dollars)

Predictor variables:
1.years of experience
2. education level (high school, college, or graduate degree).

B. Response variable: Number of Pizzas sold per week

Predictor variables:
1.city’s median income (in dollars)
2. average number of individuals for household
3. number of times per week members of the household eat in restaurants
4.preference of toppings (cheese, sausage, pepperoni, or vegetables)
5. price per pizza.

C. Response variable: Charge per customer( in thousands of dollars)

Predictor variables:
1.the number of commercial clients in an area
2. the number of residential clients in the same area
3.our average number of employees
4.the average amount charged by our top competitor
5.the average number of packages we ship per month.

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