using the following data set in R : a) Treating CBD as a 0/1 numeric variable, fit a simple linear regression that tries to predict assessed price using CBD. Is being in the CBD a significant predictor of assessed price? Give your decision where you either reject or do not reject the null, as well as the p-value on which that decision was based. b) Now treat CBD as a 2-level factor by using as.factor() in the lm() call in order to fit an ANOVA model (with 2 groups) that tries to explain variation in assessed prices using CBD group. Does CBD group explain a significant amount of the variation in assessed price? Give your decision where you either reject or do not reject the null, as well as the p-value on which that decision was based. c) Perform a Student's t-test, where your two groups are "in the CBD" and "outside of the CBD". The null is that the two groups have the same average assessed price. Give your decision where you either reject or do not reject the null, as well as the p-value on which that decision was based.

assessed	area	CBD	security
788000	76400	0	Private guards
738000	74300	0	None
646000	69600	0	Private guards
762000	73600	0	Fencing
872000	76800	0	None
706000	72700	1	None
860000	79200	0	Private guards
831000	75600	0	Fencing
945000	78100	0	Private guards
712000	76900	1	Private guards
643000	68500	0	None
731000	73200	0	None
968000	77500	0	Private guards
824000	76200	0	Fencing
816000	75100	0	None
768000	77000	1	Fencing
772000	73000	0	Fencing
737000	73000	1	Fencing
886000	77200	0	Fencing
747000	73400	0	None
912000	78800	0	None
866000	77300	0	Fencing
827000	76500	0	Private guards
878000	76800	0	Fencing
850000	79400	1	None
691000	71500	0	None
696000	70000	1	Private guards
712000	71900	0	None
629000	74700	1	Private guards
841000	76100	0	Private guards
670000	72600	1	Private guards
832000	77600	1	Fencing
639000	70700	1	Fencing
853000	76300	0	None
924000	77200	0	Private guards
903000	77900	0	None
747000	72900	0	Fencing
733000	73600	1	None
831000	75000	0	Fencing
691000	72500	0	None
750000	74100	1	None
674000	70300	1	Private guards
684000	70600	0	Fencing
793000	76900	1	Private guards
864000	75800	0	Fencing
758000	71900	0	Private guards
888000	78800	0	Fencing
727000	73500	1	Private guards
889000	78400	0	Fencing
827000	75800	0	Private guards
866000	74600	0	None
828000	76500	0	Fencing
879000	77300	0	Private guards
755000	74400	0	None
810000	71300	0	None
882000	74500	0	None
639000	69500	0	Private guards
782000	75900	0	Fencing
633000	68200	0	None
902000	78500	0	Fencing
743000	73200	0	Fencing
976000	79400	0	Fencing
844000	74700	0	Fencing
705000	71500	1	None

d) Why did I have you do the above three tests?