Use any dataset. From that dataset, select any two quantitative variables that you suspect will be related (such as age and height for example). What is the name of the dataset you have chosen? Which two variables did you choose? Next, using Excel, calculate the correlation coefficient (r-value) between the two variables. Recall that the Excel "formula" for correlation is "=CORREL". What is the r value for the two variables that you have chosen? Is it positive or negative? Is it strong, medium, or weak? Note that it is best to have an r value that is medium or strong. It is recommended that you try a few different variables until you find two variables with an r-value between .5 and 1 (or between -.5 and -1). Next, use Excel to create a scatterplot for the two variables. You decide which variable will be dependent (y) and which will be independent (x). On the scatterplot, include the "trendline" and the "equation for the line" using Excel options. Finally, using the equation of the line that you generated above, plug in any reasonable value for x (your chosen independent variable) and solve the equation for y (your chosen dependent variable). Determine which of the two variables is x and y. What prediction do you get? Show all of your work. In other words, type out the equation, plug in a value for x, and show your solution for y.