Description
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Explanation & Answer
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1-a) The least squares estimate for the regression line
Yi = β0 + β1Xi + εi
can be given as:
β1 =
𝑁 ∑ 𝑥𝑦−∑ 𝑥 ∑ 𝑦
𝑁 ∑ 𝑥 2 −(∑ 𝑥)2
β0 =
∑ 𝑦−β1 ∑ 𝑥
𝑁
So, we get the least square regression line as:
Yi = 38333.33 + 37.619Xi + εi
1-b) For a 2,000 square feet house, the estimated sale price is:
Yi = 38333.33 + 37.619*2000 = $113571.3
1-c) The error term is given as:
εi = Yi – Ŷi
X
Y
1000
1300
1600
1900
2200
2500
70000
95000
85000
125000
130000
120000
Yi
εi
75952.33 -5952.33
87238.03 7761.97
98523.73 -13523.7
109809.4 15190.57
121095.1 8904.87
132380.8 -12380.8
The standard deviation of error terms (RMSE)...