In 2000, Fortune magazine published the top 100 fastest-growing companies. The following variables were collected for each company:
1. Name
2. Earnings-per-share, 3 year annual rate (percent)
3. Net Income, past four quarters (millions of dollars)
4. Revenue growth, 3 year annual rate (percent)
5. Revenue, past four quarters (millions of dollars)
6. Total return, 3 year annual rate (percent)
7. Stock price change in past year(percent)
8. Stock price (dollars)
9. Estimated price/earnings ratio a year from now (2001)
10. Category (1=technology, 2=industrial, 3 = retail, 4 =healthcare, 5= financial services, 6 = telecommunications, 7 = other)
11. Technology Company? (1 = yes, 0 = no)
12. Industrial Company? (1=yes, 0 = no)
13. Retail Company? (1 = yes, 0 = no)
14. Healthcare Company (1 = yes, 0 = no)
15. Financial Services Company? (1 = yes, 0 = no)
16. Telecommunications Company? (1 = yes, 0 = no)
Using stock price (#8) as the outcome variable, carry out a multiple regression. The variable “category” should not be included in the model. Instead, use the dummy codes variables for each of the company types if you wish to include them in your model. You may find that you do not need to use all variables in your “best” model; just be sure to justify your variable selection (by p-values, R2, etc).
Attachment:- stats-hw-data-set.rar