In: Statistics and Probability
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): Xi |
16 |
28 |
13 |
22 |
25 |
19 |
Number of Calls: Yi |
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 β1.
Let Y: the selling price of a house,
X: its size
simple linear regression model: Y = Xβ + ε
here a= β0 & b= β1