Quiz4

# Quiz4 - E(Y|x)= μ Y|x = β β 1 x Simple Linear Regression...

This preview shows pages 1–2. Sign up to view the full content.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: E(Y|x)= μ Y|x = β + β 1 x Simple Linear Regression Model : Y= β + β 1 x+ – Assumes random, independent, mean 0, ε constant variance Method of Least Squares: Y i = β + β 1 x i + ε i , i=1, 2, …, n where: Estimated regression line is Residuals: Residual sum of squares: Unbiased estimators , meaning distributions are centered at true values of β 1 and β and are normal. (coefficient of determination) Regression models are used primarily for interpolation . That is, when predicting a new observation on the response (or estimating the mean response) at a particular value of the regressor x, we should only use values of x that are within the range of the x’s used to fit the model. Testing Hypotheses in Simple Linear Regression H : β 1 = β 1,0 , H 1 : β 1 ≠β 1,0 Test stat: (for our purposes, B 1,0 =0 usually) Reject H if To test β =/ 0: ≠ Reject null for same reason as above....
View Full Document

{[ snackBarMessage ]}

### Page1 / 2

Quiz4 - E(Y|x)= μ Y|x = β β 1 x Simple Linear Regression...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online