a. Determine the simple linear regression equation. Use formulas

b. Validate the hypothesis if there is a positive Linear Relation (Ho>0 ).

c. Using an alpha or significance level of 0.05 Test the hypothesis about the coefficient

of positive correlation to know if there is a positive relationship between income and the price of housing. (Ho >0)

d. Make a Scatter XY graph and calculate the linear regression equation and the coefficient

of determination (Using Excel)

e. For an income of $95,000 what house price would be obtained?

	X	Y	XY	X^2	Y^2
City	Income	Home Price
Akron, OH	74.1	114.9	8514.09	5490.81	13202.01
Atlanta, GA	82.4	126.9	10456.56	6789.76	16103.61
Birmingham, AL	71.2	130.9	9320.08	5069.44	17134.81
Bismark, ND	62.8	92.8	5827.84	3943.84	8611.84
Cleveland, OH	79.2	135.8	10755.36	6272.64	18441.64
Columbia, SC	66.8	116.7	7795.56	4462.24	13618.89
Denver, CO	82.6	161.9	13372.94	6822.76	26211.61
Detroit, MI	85.3	145	12368.5	7276.09	21025
Fort Lauderdale, FL	75.8	145.3	11013.74	5745.64	21112.09
Hartford, CT	89.1	162.1	14443.11	7938.81	26276.41
Lancaster, PA	75.2	125.9	9467.68	5655.04	15850.81
Madison, WI	78.8	145.2	11441.76	6209.44	21083.04
Naples, FL	100	173.6	17360	10000	30136.96
Nashville, TN	77.3	125.9	9732.07	5975.29	15850.81
Philadelphia, PA	87	151.5	13180.5	7569	22952.25
Savannah, GA	67.8	108.1	7329.18	4596.84	11685.61
Toledo, OH	71.2	101.1	7198.32	5069.44	10221.21
Washington, DC	97.4	191.9	18691.06	9486.76	36825.61