**Monday/Tuesday**

Finish Week 7/8 MOM Oxbow Correlation and Regression + quiz (due Thursday 10/21, turn in your work by the start of class on Friday 10/22)

**Wednesday/Thursday/Friday**

Learning Target:* I can find empirical and theoretical probabilities.*

We’ll watch this <link>

*We’ll collect some data and find **probabilities*

*Once we are done with the data collection, Submit your results <link>
*

Outside of class work:

I need you to watch these videos. You should take notes on pages 50-63 of the packet I gave you. Scott Stevens is a professor from Champlain College, the author of the textbook I am using with you this year.

<link>

This will enhance what we are doing in class this week.

Complete, on paper the starred exercises on p 64-70. Here are the answers Chapt 4 Answers ThinkDo Oxbow Fall 2020

Graded work

In the Canvas>Modules>Week 8> discussion forum, post your work and answer(s) to one of the unstarred exercises on pages 64-70. This is a completion grade. Challenge yourself. (20 points due by Monday 10/25)

Complete the MOM ThinkDO Chapter 4 exercises Due Wednesday (10/27) night @ Midnight.

**Updated Friday 10/22**

Outside of class work: If you would like a “requiz” on this week’s quizzes, complete the following and turn it in via Canvas>Modules>Week 8/9 ending 10/29>Optional Regression project. The old quiz grades will not be changed. If you would like it to count on Qtr 1, you’ll need to complete it by next Thursday night 10/28. If You go this route, I will move this week’s quizzews to Qtr 1, if I placed one or both into Qtr 2.

If you want this included in Qtr 2, have it turned in by Sunday night 10/31.

If you turn this in, a grade will be entered into IC, whether or not you do well on it. It is an additional grade, NOT extra credit. It will help to offset a lower grade. It is a 100 point Summative grade.

Regression Analysis:

Part 1 (before you run any analysis)

Choose two quantitative variables that you think may be associated. You can collect some data yourself or find lists on the Internet.

Before you conduct any analysis, What association ( Shape, Strength, Direction) do you expect to see between the two variables? Which variable is the explanatory variable and which variable is the response variable?

Part 2

I’ll be looking to see if the following is present and correct.

- Table of Your two quantitative variables.
- Well labeled scatterplot (Axes with units)
- Correlation coefficient (r)
- Coefficient of Determination (r
^{2}) expressed either as a proportion/percentage and you explain what it means in the context of this situation. - Least Square Regression Equation for predicting your Response Variable from your Explanatory Variable.
- An analysis of your results. You must relate your results back to part 1. This must include a discussion about r and r
^{2} - You use your model to make a prediction for two values that are not part of the original data. One of these values must be an example of extrapolation. Identify this prediction.
- Discuss what the slope and y-intercept of your model means in the context of the situation.
- You suggest possible sources of confounding influences.

You can attach a publicly share link to a google doc/sheet.