Suppose we wanted to predict the selling price of a house, using its size, in a...

Suppose we wanted to predict the selling price of a house, using its size, in a certain area

of a city. A random sample of six houses were selected from the area. The data is

presented in the following table with size given in hundreds of square feet, and sale price

in thousands of dollars.:

Temperature (^oF): X_i	16	28	13	22	25	19
Number of Calls: Y_i	95	120	70	115	130	85

We are interested in fitting the following simple linear regression model: Y = Xβ + ε

a) Calculate X′X, (X′X)^-1 and X′Y and then calculate the least squares estimates of β₀ and β_1.

Solutions

Expert Solution

Let Y: the selling price of a house,
X: its size

simple linear regression model: Y = Xβ + ε
here a= β0 & b= β1

orchestra answered 1 year ago

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