Regression

• Uses a variable (x) to predict the outcome variable (y).
• Tells how to draw straight line described by the correlation.
• Calculates ‘best-fit’ line for a certain set of data.
• Example of linear regression

a) Predict “GPA” of college students based on the “SAT” score.

b) Examine the linear relationship between “ Blood cholesterol” and “Fat intake”.

Regression coefficient

• Is a constant that represent the change in one variable (y) due to change in another variable (x).
• Coefficient are number by which variables are multiplied.

Eg: y = -3.6 + 5x₁ – 1.8x₂  [ where, 5 and 8 are coefficient]