An accounting professor is interested in quantifying the relationship between hours spent studying and total paints earned in the course (final grade). The professor collected data on 156 students who took the course the last two years (4 semesters). Answer the following: A. Create a scatterplot for the data (hint: total points earned is your response or "y" variable) A.1. Insert a linear trendline and display the equation and r-square in your chart. A.2. What does the chart tell you about the relationship between hours spent studying and total points earned in the course? B. Develop a simple regression model showing how total points earned is related to hours spent studying. What is the equation? C. How much of the variability in total points earned is explained by the hours a student spent studying in the course? (hint: predictive power) D. Interpret the results of your model. Is it a reliable model? What does the coefficient for hours spent studying tell you about total points earned? E. Suppose a student spent 80 hours studying for the course in a semester. Use your regression equation to estimate the total points earned. F. Calculate the 95% lower and upper bounds (also called the 95% confidence interval) for total points earned for the student in E above. (hint: remember the empirical rule: "mean +/- 2*standard deviation")