Linear Regression

Linear Regression

1. assumptions

   • linear relationship between x and y

2. assumptions

3. Assumptions

   • Linear relationship between x and y
   • observations are independent
   • residuals are normally distributed
   • residuals have the same variability
   • x variable measured without error

4. Computation

   • Y=b0+b1 (x)
     • Y = dependant variable
     • b1 = summation of (x-x mean) (y-y mean) divided by summation of (x-x mean) squared
     • b0 = subtitute the variable
     • Linear Regression Graph