Step 1: Collect and organize your data. ⦁ Using the Super Survey Simulator, survey 10 students of your choice and gather data. Create an organized representation of your data below. ⦁ 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. ⦁ How do you calculate the residuals for a scatterplot? ⦁ Calculate the residuals for your scatterplot in step 2d. ⦁ Create a residual plot for your data. ⦁ 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.