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Regression and beta values

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2. Before dinner, you run an OLS regression with the data below and commit the estimated beta values to memory.
X Y
2 6
4 17
5 16
8 20
2 8

While watching television after dinner, you suffer memory loss. You can't remember what show you just watched or what you ate for dinner. What's worse, you can no longer remember whether beta-0=4.2 and beta-1=2.2, or whether it was the other way around (beta-0=2.2 and beta-1=4.2). You can't rerun the regression, because you have forgotten the password to your computer. And, incredibly, you can't remember the formula for computing beta-1 by hand, something you were sure you would remember for the rest of your life.

How can you still figure out which is the correct pair of values for beta-0 and beta-1?

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Solution Summary

This solution looks at a OLS regression and how to calculate the correct beta values.

Solution Preview

One property of an ordinary least squares regression is that the regression line passes through the means of the observed values:
y-average = beta-0 + beta-1 * ...

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