Assign the values 1, 2, 3…, 26 to A, B, C…, Z respectively

Assign the values 1, 2, 3…, 26 to A, B, C…, Z respectively.

A (1) B (2) C (3) D (4) E (5) F(6) G(7) H (8) I (9) J (10) K (11) L (12) M (13) N (14 (1) O(15) P(16) Q (17) R (18) S (19) T (20) U(21) V(22 ) W (23) X (24) Y (25) Z(26)

Find the value of (F+L) *1000, where F is the first letter of your first name and L is the last letter of your first name.

ADD this number to each number in the Sale Price column. Label the new Sale Price Column as FLY.

Example: My first name- MAHESH

I will use M for F, H for L

M=13. H=8. So I will add 21,000 to each value in sale price column and label the revised sale prices as MHY.

FLY = New Sale Price ($), X1= No. Apartments, X2= Age of Structure, X3= Lot Size

X4= No. of Parking Spaces, X5= Gross Building Ares( sq. ft.)

a. Analyze the data, using FLY as the dependent variable and X1, X2, X3, X4, X5 as independent variables.

i. Is the fitted model useful? Use α=0.5
j. ii.. Which terms in the model are useful ? Use α=0.05

b. Analyze the same data, using FLY as the dependent variable and X1, X2, X3, X4, X5 and condition as independent variables. Is this model better than the first model for predicting sale price? Use 5% level of significance.

Project 2 Data
	Sale	Number of	Age of	Lot	Number of	Gross	Building
Building No.	Price	Apartments	Structure	Size	Parking Spaces	Building area	Condition
1	90300	4	82	4365	0	4266	F
2	384000	20	13	17798	0	14391	G
3	157500	5	66	5913	0	6615	G
4	676200	26	64	7750	6	34144	E
5	165000	5	55	5150	0	6120	G
6	300000	10	65	12506	0	14552	G
7	108750	4	82	7160	0	3040	G
8	276538	11	23	5120	0	7881	G
9	420000	20	18	11745	20	12600	G
10	950000	62	71	21000	3	39448	G
11	560000	26	74	11221	0	30000	G
12	268000	13	56	7818	13	8088	F
13	290000	9	76	4900	0	11315	E
14	173200	6	21	5424	6	4461	G
15	323650	11	24	11834	8	9000	G
16	162500	5	19	5246	5	3828	G
17	353500	20	62	11223	2	13680	F
18	134400	4	70	5834	0	4680	E
19	187000	8	19	9075	0	7392	G
20	155700	4	57	5280	0	6030	E
21	93600	4	82	6864	0	3840	F
22	110000	4	50	4510	0	3092	G
23	573200	14	10	11192	0	23704	E
24	79300	4	82	7425	0	3876	F
25	272000	5	82	7500	0	9542	E
	F	Fair	G	Good	E	Excellent