Suppose the simple linear regression model, Yi = β0 + β1 xi + Ei, is used to explain the relationship between x and y. A random sample of n = 12 values for the explanatory variable (x) was selected and the corresponding values of the response variable (y) were observed.  A summary of the statistics is presented in the photo attached. Let b1 denote the least squares estimator of the slope coefficient, β1. What is the value of b1?

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Suppose the simple linear regression model, Yi = β0 + β1 xi + Ei, is used to explain the relationship between x and y. A random sample of n = 12 values for the explanatory variable (x) was selected and the corresponding values of the response variable (y) were observed. 

A summary of the statistics is presented in the photo attached.

  1. Let b1 denote the least squares estimator of the slope coefficient, β1. What is the value of b1?
Σ
.-2 Σu= 5. Σε 32. Σ4 15, Σ =
x = 135, > y = 1025
Transcribed Image Text:Σ .-2 Σu= 5. Σε 32. Σ4 15, Σ = x = 135, > y = 1025
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