STAT 440 - Forecasting
Lecture Review #5 - Least Squares

Review questions:

1) What is the least squares principle in statistics?

Computational exercises:

The standard linear regression model uses both a slope and an intercept. However, occasionally it is useful to use an interceptless model - that is, simply to model the data as

Y = β₁*X + ε

where ε is an error term. This forces the line to pass through the origin - there is no intercept.

You are asked to derive the least squares estimate b₁for the slope parameter β₁. DO THIS FROM FIRST PRINCIPLES - that is, actually find the derivative, etc. - don't just make a mathematical substitution into existing formulas.

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