Step 1: Collect and organize your data.

a) Using the Super Survey Simulator, survey 10 students of your choice and gather data. Create an organized representation of your data below.



















b) What do you think the purpose of this survey is? Explain.









Step 2: Graph your data.

After organizing your data, you will now create a graphical representation of your data.

Why is a scatterplot an appropriate display for this data set?




What features would need to be included on a scatterplot so that the data can be easily analyzed? Make a list of needed features and explain why each is important to the graph.







Next, you will make a scatterplot. Name a point that will be on your scatterplot and describe what it represents.







Using the regression calculator in your tool bar, create a scatterplot using your data set from step 1. Insert a screenshot of your scatterplot, or recreate it below.





Step 3: Analyze your data.

Now that you have represented your data graphically, it can be more easily analyzed.

Describe how the line of best fit and the correlation coefficient can be used to determine the correlation between the two variables on your graph.








Describe the type of correlation between the two variables on your graph. How do you know?








Does the correlation between the variables imply causation? Explain.








d) How do you calculate the residuals for a scatterplot?











e) Calculate the residuals for your scatterplot in step 2d.














f) Create a residual plot for your data.

























g) Does your residual plot show that the linear model from the regression calculator is a good model? Explain your reasoning.







Step 4: Make a prediction with your data.

Using your equation from step 2d, estimate the GPA of a student who studies for 15 hours a week. Justify your answer