Consider the real estate data on 60 homes in a middle class neighborhood of Southwest Houston provided on the Excel data file. The variables are:

Price (Y) in $1000, Square Feet (X1), # of Rooms (X2), # of Bedrooms (X3), # of Bathrooms (X4), Age (X5)

A. Construct Scatter plot of all 5 variables (one at a time) vs. Price (Y) (5 graphs), insert best fitted linear equations and comment on the goodness of the fit based on R-squared values.

B. Construct the correlation matrix of all 6 variables and rank variables based on correlations with Price. Discuss correlation of variables against Price in plain language.

C.Construct a full model using all independent variables vs. Price (Y), find the equation, R-squared, significant F, and comment on the goodness of the model.

D.In part C, rank the independent variables based on degree of contribution to the model (use P-values). Pick the top 4 variables based on P-values and construct a 4 variable multiple linear regression model to predict Price. Make sure to obtain residual values in the model. Find the regression equation, R-squared, significant F, and comment on the goodness of the model.

E.Use the residuals output in part (d) and identify top 5 overvalued and 5 undervalued homes in this neighborhood.

F. Based on model in part (d), estimate the value for 3700 sq. ft. home with 6 rooms, 3.5 baths, 4 bedrooms, and age of 15.

		Measurements taken on 60 single-family homes
			sales price ($1000)
		Home	Price	Sq. Feet (X1)	# of Rms (X2)	# of Bedrms (X3)	# of BathRms (X4)	Age (X5)
		1	395	2655	6	3	2	35
		2	367	2347	7	4	2.5	36
		3	377	2596	9	3	3	36
		4	373	2687	6	4	2	41
		5	386	2197	7	4	2.5	40
		6	405	2197	6	4	2	10
		7	562	3976	9	5	3	64
		8	596	3889	8	4	4	19
		9	491	3286	6	4	2.5	16
		10	349	2603	6	4	2	37
		11	299	2352	5	3	2	41
		12	371	2855	7	4	2.5	35
		13	714	3501	9	4	3	52
		14	898	4738	8	4	3.5	12
		15	590	4907	10	5	4.5	76
		16	436	2653	7	4	3	52
		17	426	2246	6	3	2	69
		18	689	3927	8	4	3.5	67
		19	556	2358	7	4	3	11
		20	838	5581	8	4	4.5	9
		21	608	3968	6	3	2.5	14
		22	559	2854	6	4	2	11
		23	646	3448	6	4	2.5	14
		24	522	2592	10	4	3.5	16
		25	491	2690	7	4	2.5	27
		26	454	2855	6	3	2.5	35
		27	482	3334	6	4	4	20
		28	281	2075	6	3	2.5	74
		29	836	5587	10	5	3	15
		30	635	3066	6	4	2	15
		31	411	1876	7	4	2.5	16
		32	454	2933	6	3	2	24
		33	436	3113	7	4	2.5	26
		34	275	2170	4	4	2.5	42
		35	386	2911	6	3	3.5	9
		36	528	3707	7	4	3	30
		37	640	4476	9	5	2.5	39
		38	436	3420	8	5	3.5	32
		39	516	2981	6	3	2.5	24
		40	504	3183	9	5	3	74
		41	578	3720	7	4	2	14
		42	621	4127	8	4	3	16
		43	578	3055	7	4	3.5	12
		44	776	4913	9	5	3.5	12
		45	374	2645	6	3	2.5	34
		46	406	3050	7	4	3	29
		47	442	3540	6	4	3.5	33
		48	974	5876	8	4	4.5	2
		49	436	2777	7	4	2.5	36
		50	683	4539	9	4	4	37
		51	340	2050	6	4	2.5	27
		52	405	3001	8	4	3	79
		53	395	2710	6	4	2.5	20
		54	466	2344	6	4	2.5	2
		55	516	2540	6	4	2.5	2
		56	312	2498	7	4	2.5	43
		57	937	5654	13	5	4.5	62
		58	485	3840	7	4	3.5	29
		59	931	5576	7	4	3	4
		60	405	2068	6	3	2.5	21