1.Download the "cars.xlsx" dataset from the course D2L shell.This dataset includes data on the 0-60 time (TIME), top speed (SPEED), curb weight (WEIGHT), and horsepower (HP) of 30 automobiles.For full credit, in addition to providing your answers below, include your Excel spreadsheet with your scatter plot from a and regression output as part of your submission to the dropbox.

a.What is the expected effect of increasing horsepower on 0-60 time?

b.Using Excel, scatter plot of TIME (dependent variable, y-axis) and HP (independent variable, x-axis).Add a linear trendline to your scatter plot. Does your scatter plot confirm your prediction in (a)?

c.Estimate the regression TIME_i=₀+ ₁HP_i+

d.Interpret your estimated coefficient on HP.(That is, in words, what does the value tell you?)Interpret the R²from your regression.

e.Estimate the regression TIME_i=₀+ ₁HP_i+ ₂WEIGHT_i+

f.Interpret your estimated coefficient on WEIGHT.(That is, in words, what does the value tell you?)Does the sign of this coefficient match your expectations?What happened to the adjusted R²when WEIGHT was added to this regression?What does this tell you?

2.In an effort to determine whether going to class improved student academic performance, David Romer[1]developed the following equation:

Where:G_i= the grade of the ith student in Romer's class (A=4, B=3, etc).

ATT_i= the percent of class lectures that the ith student attended

PS_i= the percent of the problem sets that the ith student completed

a.What signs do you expect for the coefficients of the independent variables in this equation?Explain your reasoning.

b.Romer then estimated the equation:

Do the estimated results agree with your expectations?

c.It's usually easier to develop expectations about the signs of coefficients than about the size of those coefficients.To get an insight into the size of the coefficients, let's assume that there are 25 hours of lectures in a semester and that it takes the average student approximately 50 hours to complete all of the problem sets in a semester.If a student in one of Romer's classes had only one more hour to devote to class and wanted to maximize the impact on his or her grade, should the student go to class for an extra hour or work on problem sets for an extra hour?Explain your answer. (HINT:Convert the extra hour to percentage terms and then multiply those percentages by the estimated coefficients.)

d.From the given information, it would be easy to draw the conclusion that the bigger a variable's coefficient, the greater its impact on the dependent variable.To test this conclusion, what would your answer to part c have been if there had been 50 hours of lecture in a semester and if it had taken 10 hours for the average student to complete the problem sets?Were we right to conclude that the larger the estimated coefficient the more important the variable?

e.What's the real world meaning of R²= 0.33?For this specific equation does 0.33 seem high, low or about right?

f.Is it reasonable to think that only class attendance and problem set completion affect your grade in a class?If you could add just one more variable to the equation, what would it be?Explain your reasoning.What should adding your variable to the equation do to R²? To adjusted-R²?

[1]Romer, David.(1993).Do Students Go to Class?Should They?Journal of Economic Perspectives7(3): 167-74.

N22 X V fx A B C D E F G OBS MAKE MODEL TIME SPEED WEIGHT HP 1 Audi TT Roadster 8.9 133 1335 150 2 Mini Cooper S 7.4 134 1240 168 3 Volvo 070 T5 Sport 7.4 150 1711 4 Saab 220 Nine-Three 7.9 149 1680 247 5 Mercedes-Benz SL350 6.6 155 1825 268 6 Jaguar XKB 6.7 154 1703 290 7 Bugatti Veyron 16.4 2.4 253 1950 1000 8 Lotus Exige 4.9 147 875 189 9 BMW M3 (E30) 6.7 144 10 BMW 1257 220 11 330i Sport 5.9 155 1510 12 11 Porsche 231 Cayman S 5.3 171 1350 13 291 12 Nissan Skyline GT-R (R34) 4.7 165 1560 14 13 Porsche 276 911 RS 4.7 172 1270 300 15 14 Ford Shelby GT 5 150 1584 18 15 Mitsubishi 319 Evo VII RS Sprint 4.4 17 150 1260 16 Aston Martin 320 VB Vantage 5.2 175 1630 18 17 Mercedes-Benz 380 SLK55 AMG 4.8 155 1540 355 19 18 Maserati Quattroporte Sport GT 5.1 171 1930 394 20 19 Spyker CB 4.5 21 20 Ferrari 187 288GTO 1275 400 4.9 189 1161 400 22 21 Mosler MT900 3.9 190 1130 23 22 Lamborghini 435 Countach QV 4.9 180 24 23 Chrysler 1447 455 Viper GTS-R 4 190 25 24 Bentley 1290 460 Amage T 5.2 26 179 2585 25 Ferrari 500 430 Scuderia 3.5 198 503 26 Saleen 1350 27 3.3 240 28 27 Lamborghini 1247 550 Murcielago 4 29 205 1650 28 Pagani 570 Zonda F 3.6 214 1230 30 602 29 Mclaren F1 3.2 31 240 1140 30 Koenigsegg CCR 627 3.2 242 1180 806 32 33