Today will continue to talk about best fit lines and learn the least squares regression equation.
The opener will again be practicing finding x and f(x), but in the context of a best fit line.
Our lesson will continue with the air travel situation but in a Part 2 of the Air Travel Activity Builder. We'll now focus on a "best" fit line over a "hey, it looks good" fit line, and talk about what the correlation coefficient means. I really think the idea behind this one is sound, but I think the execution of it still needs a lot of work. Suggestions appreciated.
For homework they will complete a linear regression application problem. I think this one is pretty good, but it may be a case of me really liking it and the students not so much. We'll see.