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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...

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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?
. 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 co
ect 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?
. 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 XXXXXXXXXXUse 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
    Team    Conference    Yds/Att    Int/Att    Win%
    Arizona Cardinals    NFC    6.5    0.042    50.0
    Atlanta Falcons    NFC    7.1    0.022    62.5
    Carolina Panthers    NFC    7.4    0.033    37.5
    Cincinnati Bengals    AFC    6.2    0.026    56.3
    Detroit Lions    NFC    7.2    0.024    62.5
    Green Bay Packers    NFC    8.9    0.014    93.8
    Houstan Texans    AFC    7.5    0.019    62.5
    Indianapolis Colts    AFC    5.6    0.026    12.5
    Jacksonville Jaguars    AFC    4.6    0.032    31.3
    Minnesota Vikings    NFC    5.8    0.033    18.8
    New England Patriots    AFC    8.3    0.020    81.3
    New Orleans Saints    NFC    8.1    0.021    81.3
    Oakland Raiders    AFC    7.6    0.044    50.0
    San Francisco 49ers    NFC    6.5    0.011    81.3
    Tennessee Titans    AFC    6.7    0.024    56.3
    Washington Redskins    NFC    6.4    0.041    31.3

Data
    Hours Spent Studying    Total Points Earned
    22    12
    20    18
    29    25
    24    25
    43    28
    46    29
    39    35
    40    39
    51    40
    43    43
    39    43
    51    49
    52    50
    65    51
    57    53
    56    53
    52    55
    66    55
    63    57
    68    57
    67    59
    42    59
    65    59
    69    60
    72    60
    66    61
    53    61
    45    61
    58    62
    81    62
    60    62
    57    62
    77    62
    78    63
    67    64
    78    64
    72    64
    58    64
    71    65
    76    65
    79    66
    83    66
    65    66
    72    66
    71    66
    52    67
    78    67
    70    67
    81    67
    80    68
    79    68
    72    68
    75    68
    91    68
    65    68
    84    69
    77    69
    78    70
    72    70
    84    70
    83    70
    67    70
    80    71
    78    71
    72    72
    70    72
    94    72
    92    72
    84    73
    98    73
    78    73
    78    73
    84    73
    74    74
    90    74
    83    74
    84    74
    83    75
    78    75
    93    75
    80    75
    101    76
    81    76
    83    76
    91    76
    83    76
    93    76
    78    76
    78    77
    65    77
    84    77
    97    77
    88    77
    93    78
    93    78
    95    78
    95    79
    91    79
    95    79
    94    79
    95    80
    102    80
    105    80
    83    80
    99    80
    97    81
    79    81
    101    81
    88    82
    93    83
    95    85
    94    85
    104    85
    88    85
    80    86
    98    86
    83    86
    91    86
    90    87
    83    87
    92    88
    88    88
    99    89
    101    90
    101    90
    99    90
    102    90
    84    90
    110    91
    93    91
    105    91
    109    91
    91    92
    104    92
    95    92
    98    92
    91    93
    104    93
    104    94
    106    95
    95    95
    106    95
    92    95
    101    96
    95    96
    109    96
    95    96
    101    96
    105    97
    104    97
    104    97
    105    98
    95    99
    109    100
    110    100
    101    100
Answered Same Day Jul 16, 2022

Solution

Prateek answered on Jul 17 2022
66 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.
. 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 e
or 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 E
o
    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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