BUS 538_Spring 2022 Assignments 5&6 (Due on 5/8) ** PLEASE NOTE: You don’t need to record a video for this assignment** 1. Studying and Grades. A marketing professor at Givens College is interested in...

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BUS 538_Spring 2022 Assignments 5&6 (Due on 5/8) ** PLEASE NOTE: You don’t need to record a video for this assignment** 1. Studying and Grades. A marketing professor at Givens College is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 156 students who took the course last semester are provided in the file MktHrsPts. a. Develop a scatter chart for these data. What does the scatter chart indicate about the relationship between total points earned and hours spent studying? b. Develop an estimated regression equation showing how total points earned is related to hours spent studying. What is the estimated regression model? c. Test whether each of the regression parameters β0 and β1 is equal to zero at a 0.01 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable? d. How much of the variation in the sample values of total point earned does the model you estimated in part (b) explain? e. Mark Sweeney spent 95 hours studying. Use the regression model you estimated in part (b) to predict the total points Mark earned. f. Mark Sweeney wants to receive a letter grade of A for this course, and he needs to earn at least 90 points to do so. Based on the regression equation developed in part (b), how many estimated hours should Mark study to receive a letter grade of A for this course? 2. NFL Winning Percentage. The National Football League (NFL) records a variety of performance data for individuals and teams. To investigate the importance of passing on the percentage of games won by a team, the following data show the conference (Conf), average number of passing yards per attempt (Yds/Att), the number of interceptions thrown per attempt (Int/Att), and the percentage of games won (Win%) for a random sample of 16 NFL teams for the 2011 season (NFL web site). a. Develop the estimated regression equation that could be used to predict the percentage of games won, given the average number of passing yards per attempt. What proportion of variation in the sample values of proportion of games won does this model explain? b. Develop the estimated regression equation that could be used to predict the percentage of games won, given the number of interceptions thrown per attempt. What proportion of variation in the sample values of proportion of games won does this model explain? c. Develop the estimated regression equation that could be used to predict the percentage of games won, given the average number of passing yards per attempt and the number of interceptions thrown per attempt. What proportion of variation in the sample values of proportion of games won does this model explain? d. The average number of passing yards per attempt for the Kansas City Chiefs during the 2011 season was 6.2, and the team’s number of interceptions thrown per attempt was 0.036. Use the estimated regression equation developed in part (c) to predict the percentage of games won by the Kansas City Chiefs during the 2011 season. Compare your prediction to the actual percentage of games won by the Kansas City Chiefs. (Note: For the 2011 season, the Kansas City Chiefs’ record was 7 wins and 9 losses.) e. Did the estimated regression equation that uses only the average number of passing yards per attempt as the independent variable to predict the percentage of games won provide a good fit? Data TeamConferenceYds/AttInt/AttWin% Arizona CardinalsNFC6.50.04250.0 Atlanta FalconsNFC7.10.02262.5 Carolina PanthersNFC7.40.03337.5 Cincinnati BengalsAFC6.20.02656.3 Detroit LionsNFC7.20.02462.5 Green Bay PackersNFC8.90.01493.8 Houstan TexansAFC7.50.01962.5 Indianapolis ColtsAFC5.60.02612.5 Jacksonville JaguarsAFC4.60.03231.3 Minnesota VikingsNFC5.80.03318.8 New England PatriotsAFC8.30.02081.3 New Orleans SaintsNFC8.10.02181.3 Oakland RaidersAFC7.60.04450.0 San Francisco 49ersNFC6.50.01181.3 Tennessee TitansAFC6.70.02456.3 Washington RedskinsNFC6.40.04131.3 Data Hours Spent StudyingTotal Points Earned 2212 2018 2925 2425 4328 4629 3935 4039 5140 4343 3943 5149 5250 6551 5753 5653 5255 6655 6357 6857 6759 4259 6559 6960 7260 6661 5361 4561 5862 8162 6062 5762 7762 7863 6764 7864 7264 5864 7165 7665 7966 8366 6566 7266 7166 5267 7867 7067 8167 8068 7968 7268 7568 9168 6568 8469 7769 7870 7270 8470 8370 6770 8071 7871 7272 7072 9472 9272 8473 9873 7873 7873 8473 7474 9074 8374 8474 8375 7875 9375 8075 10176 8176 8376 9176 8376 9376 7876 7877 6577 8477 9777 8877 9378 9378 9578 9579 9179 9579 9479 9580 10280 10580 8380 9980 9781 7981 10181 8882 9383 9585 9485 10485 8885 8086 9886 8386 9186 9087 8387 9288 8888 9989 10190 10190 9990 10290 8490 11091 9391 10591 10991 9192 10492 9592 9892 9193 10493 10494 10695 9595 10695 9295 10196 9596 10996 9596 10196 10597 10497 10497 10598 9599 109100 110100 101100
assignments-56-1-jzfcivsz.docx nflpassing1-3f4xnwmx.xlsx mkthrspts1-3whdur33.xlsx
Answered Same DayJul 16, 2022

Answer To: BUS 538_Spring 2022 Assignments 5&6 (Due on 5/8) ** PLEASE NOTE: You don’t need to record a video...

Prateek answered on Jul 17 2022
63 Votes
1. Answers
a. The scatter plot is given as follows:
There is a direct linear relationship between the hour spent studying and total points. It means as the number of hours spent on studying increases, the total points of the students also increased.
b. The estimated regression equation will be modelled as: y = bx +a + e; wherein, y is the dependent variable, which is the total points earned in this case, ‘x’ is the independent variable which is the hours spent studying, ‘b’ is the slope of the equation that determines the change in y due to a unit change in x, ‘a’ is the intercept of dependent variable and ‘e’ is the error term of the equation.
Use the Excel regression model, the estimated regression statistics are as follows:
    Regression Statistics
    Multiple R
    0.909786
    R Square
    0.82771
    Adjusted R Square
    0.826592
    Standard Error
    7.177298
    Observations
    156
Here, Multiple R represents the goodness of fit of the equation, the higher the value, the better and it reaches 1 to the max.
R-squared determines the portion of dependent variable which is explained by the independent variable. Here, 82.77% of the dependent variable is explained by the independent variable. Rest of the variable are explained in the excel sheet attached with the assignment.
c. As per the regression model developed in part b, the 99% confidence interval for B1 is 0.7245 and 0.8782. Here, t-test has to be applied to test the regression parameter, wherein both B0 and B1 will be put equal to zero in null and alternate hypothesis as follows:
H0: B1 = 0
Ha: B0 ≠ 0
        Now, using the intercept on the lower range and upper range of the 99% confidence interval, which is 2.29 and 15.05, respectively, it is concluded that the null hypothesis is rejected and implies that the number of hours spent on studying is a good predictor of the total points earned.
d. The R-squared shows the variation in the parameter. Here, 82.77% of the dependent variable is explained by the independent variable.
e. The total points earned by mark are computed as follows:
Y = a +...
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