Math 209 Lecture 17 - Regression Analysis and Intro to Probability

In this lecture, we apply what we learned in the last lecture to find a regression line - the line of best fit to a scatter plot. We derive the formula and use the regression line to make predictions on "future" data points.

Afterwards, we switch gears and move on to probability. We start out vaguely, trying to get our intuition about what probability is...and then we do some problems, including the Monty Hall problem, to show how intuition can lead you astray!

[countingpebbles]

Great video thus far professor. Quick question at 27:00 we begin discussing making predictions using the regression line. The future value you mention is outside of the data set, isn't this a case of overfitting? I thought we could only make predictions for values in our dataset because we cannot assume that the values outside will behave in a similar manner. For ex, if our data set ranges in the X axis from 0-50 we can only make predictions inside that interval. Thanks for taking the time to read my comment.