Breakdown of R^2

from 0 to 0.2(poor)

from 0.2 to 0.4(decent)

from 0.4 to 0.6(good)

from 0.6 to 0.85(very good)

from 0.85 to 1(excellent)

Upload US crime data and focus on the state of Illinois. Your job is to "cut-&-paste" the data and create 7 columns and label them Murder, Rape, Robbery, Assault, Burglary, Larceny, and Car Theft respectively. Next perform a regression to predict the Car Theft using the remaining 6 variables. Finally, pick the two variables with the best P- values and create a new table, this time using these two variables in order to predict the Car Theft count. Answer the questions using this new table only:

DATA: https://www.limes.one/Content/DataFiles/US_CRime.txt

I) What are the two variables you picked?

a. Burglary and Robbery

b. Larceny and Car Theft

c. Robbery and Assault

d. Murder and Larceny

e. None of the above

II) After getting the new table, choose the variable with larger coefficient and chose the best interpretation.

a. Larceny; On average as the Larceny count increases so does the Car Theft count

b. Robbery; On average, as the Robbery count increases so does the Car Theft count

c. Burglary; On average, as the Burglary count increases so does the Car Theft count

d. Murder; On average, as the Murder count increases so does the Car Theft count

e. Rape; On average, as the Rape count increases so does the Car Theft count

III) How good is the fit and why?

a. Excellent, R-squared is above 0.85

b. Excellent, P-value is below 0.05

c. Excellent, Both P-values are very small

d. None of the above

IV) Which of the two variables has a better P-value?

a. Rape

b. Larceny

c. Robbery

d. Assault

e. None of the above