Choose an affluent community and retrieve information about single family home listings from a real estate website. Retrieve needed information and perform the following tasks.

1. Please construct the descriptive statistics of the data before data analysis entails the following.
2. Develop a regression model in which living area is one independent variable, lot size is the other independent variable, and home price is the dependent variable. State the hypotheses on the coefficients, justify formulation of these hypotheses, and interpret the results. Use = .05. Include all phases of assessment of the model and do not forget to check multicollinearity.
3. Now include dummy variables in the model to reflect the effect of having a pool, and the effect of view. Repeat the steps mentioned in parts (a) and (b) for this case. Descriptive statistics in this case should be categorized by the values of the dummy variable. How different the model becomes when you include the effect of having a pool and view?
4. Provide a detailed description of how adding the pool as a dummy variable impacts the coefficient of determination.
5. Choose a hypothetical living area and lot size to find the expected value - predicted listing price with and without a pool. Comment on your results.

House	Price $1000	Bedroom	Lot size
1	359.90	4	1.43
2	639.00	3	1.14
3	748.00	5	3.4
4	649.90	4	2.35
5	489.00	3	2.48
6	750.00	4	2.93
7	540.00	3	2.13
8	430.00	4	1.13
9	549.90	3	2.71
10	699.90	4	1.52