Problem 1

You are provided with a data representing various metrics from a sample of 1000 companies. This dataset includes both financial and operational variables, and your task is to understand how these factors collectively influence a company's annual revenue. The data is in the fileMetrics.xlsxand consists of the following variables,

Dependent Variable:

Annual Revenue (in m$)

Represents the total revenue generated by a company in a year.

Independent Variables:

Marketing Spend (in '000$)	Budget allocated to marketing activities.
R&D Spend (in '000$)	Investment in research and development.
Number of Employees	The total number of employees in the company.
Years in Business	The number of years the company has been operational.
Average Employee Experience (in years)	The average work experience of employees.
Region_North	Indicator variable that equals 1 if the company is in the North region of the country, 0 if it is in any other region. [Please note that we have not yet studied 'indicator variables' in class so please do not worry about the interpretation of this variable and it's coefficient, simply treat it as any other variable]

Run a regression with "Annual Revenue" as the dependent variable. As independent variables include all the other variables, and then answer the following questions.

(a) Copy and paste your regression output.

(b) Write down and interpret the coefficient on "Years in Business".

(c) Test the hypothesis that "Avg Employee Experience" has no influence upon "Annual Revenue".

(d) Test the hypothesis that an increase in R&D Spend of a 1000$ corresponds to a 0.30 m$ increase in "Annual Revenue", all other variables kept constant.

(e)What impact does the "Number of Employees" have on "Annual Revenue". Please answer citing appropriate statistics from your regression output.