Part 1

do a sca8er plot of the data. Make sure to label the axes of the graph and do a consistent scale. Make sure to give your sca8erplot a +tle. You can do by hand or by using Excel. If you choose to use Excel, here's a video that will help you to do the sca8erplot: h8ps://www.youtube.com/watch? v=MfEAEmdFOBo

Using only the graph, do a paragraph that addresses the following ques+ons:

Does there appear to be a linear rela+onship between x and y? How can you tell?

Does the rela+onship appear to be posi+ve or nega+ve? How can you tell?

Does the rela+onship appear to be strong or weak? How can you tell?

Part 2

Calculate the correla+on coefficient, r and the coefficient of determina+on, r2. here's another resource with the process in case you need a reminder: h8ps://www.mathbootcamps.com/find-the-correla+on-coefficient-r-on-your- calculator-+83-84/

do a paragraph that addresses the following ques+ons:

What is the value of the correla+on coefficient?

Does the correla+on coefficient confirm the strength (weak or strong) and direc+on (posi+ve or nega+ve) you from your sca8erplot in Part 1? Describe how you know.

Interpret the meaning of the coefficient of determina+on, r2, within the context of your data.

Part 3

Determine the equa+on of the regression line, y=b0+b1x. here's another resource with the process in case you need a reminder: h8ps://www.youtube.com/watch?v=LVnHpmbv7Yg

What value is the slope (b1) of the linear regression line? Describe what the slope means within the context of your data set. Your instructor will review how to describe this in class but if you need an addi+onal resource, click this link: h8ps://www.khanacademy.org/math/ap-sta+s+cs/ bivariate-data-ap/least-squares-regression/v/interpre+ng-slope-of-regression-line

What is the value of the y-intercept (b0)? Describe what this value means within the context of your data set. Your instructor will review how to describe this in class but if you need an addi+onal resource, click this link: h8ps://www.khanacademy.org/math/ap-sta+s+cs/bivariate- data-ap/least-squares-regression/v/interpre+ng-y-intercept-in-regression-model

Describe how you could use the equa+on of the linear regression line to predict values not included in the data set. Then pick an x-value outside your given data set and use the equa+on to calculate the predicted y-value. You can choose any x-value you want as long as it is not included in the given data set.