Instructions for Excel Practical: First attempt the linear regression task. Please use the data that is on the following slide, titled "Assignment Data' to complete the first part of the assignment. Then follow up with the next two tabs to perform a multiple regression using Excel. The first multiple regression example is already completed for you in the Lecture. Part 1: Complete the following Task Create a scatterplot of the data on the next tab. Be sure to label the axes and include a regression line. Be sure to include the equation and r- squared value and place it on the top right of the graph. Part 2: Interpret your results: please type in your answers to the following questions. Be sure to fully elaborate on them and try to include at least 2-3 sentences to explain each part. A. What kind of correlation ( positive, negative, or no correlation) exists between the MPG of a car and its acceleration time? Is it a strong correlation? B. What are the degrees of freedom of the date set? Using the critical values table in the Lecture, is the R-squared Statistic significant enough for us to make any statistical inferences? If not, how large should the sample be to substantiate the results of this study? C. Should we interpret the y-intercept in this case? Why or why not? D. Using your equation, predict the MPG of a car that accelerates in 7.5 seconds. E. In a few sentences, summarize the findings of this study? What effect does MPG consumption have on the acceleration time of a vehicle?A B C D F Acceleration MPG G H I 2 J Honda Accord Hybrid EX K M 7.4 N P 3 47 Toyota Camry Hybrid LE Data retrieved from: https://www.consumerreports.org/fuel-economy-efficiency/vehicle-fuel-economy-vs-performance/ O 7.8 4 47 Chevrolet Malibu Hybrid 8 5 41 Hyundai Sonata Hybrid SE 8.2 6 39 Ford Fusion SE Hybrid 8.3 7 39 Toyota Camry LE (4-cyl. ) 8 8 Nissan Altima 2.5 SV 32 7.6 31 Honda Accord EX (1.5T) 7.7 10 31 Chevrolet Malibu LT (1.5T) 8.4 11 29 Kia Optima EX (4-cyl. ) 8 12 28 Hyundai Sonata SEL (4-cyl. ) 8.3 13 28 Volkswagen Passat SE (4-cyl. ) 8.6 14 28