Can the cost of flying a commercial airliner be predicted using regression analysis? If so, what variables are related to this cost? A few of many variables that can potentially contribute are type of plane, distance, number of passengers, amount of luggage/freight, weather condition, direction of destination, or even pilot skill. Suppose a study is conducted using only Boeing 737s traveling 800 km on comparable routes during the same season of the year. Can the number of passengers predict the cost of flying such routes? It seems logical that more passengers result in more mass and more baggage, which could, in turn, result in increased fuel consumption and other costs. Suppose the data displayed below are the cost and associated number of passengers for thirty-six 800-km commercial airline flights using Boeing 737s during the same season of the year. We will use these data to develop a regression model to predict cost by number of passengers. The data in the .csv file contains the data on the cost and number of passengers of 36 observations. (a) Use software to estimate this model. Use three-decimals each of your least-squares estimatesyour answer. Cost , Number of Passengers, (b) Find the coefficient of determination. Expresses as a percentage, and use two decimal places in your answer. 曲 % (c) In the context of the data, interpret the meaning of the coefficient of determination. OA. The percentage found above is the percentage of variation in the number of passengers that can be explained by its linear dependency with the cost of flying a 800-km commercial flight using Boeing 737s. OB. There is a strong, positive linear relationship between the cost of flying a 800-km commercial flight using Boeing 737s and the number of passengers. OC. The percentage found above is the percentage of variation in the cost of flying a 800-km commercial flight using Boeing 737s that can be explained by its linear dependency with the number of passengers. There is a weak, positive linear relationship between the cost of flying a 800-km commercial flight using Boeing 737s and the number of passengers.
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
The following is the data. Please use R-Studio. Thanks!
|
Cost |
Passengers |
1 |
3.7 |
63 |
2 |
6.01 |
86 |
3 |
4.16 |
73 |
4 |
5.7 |
80 |
5 |
5.78 |
91 |
6 |
5.1 |
68 |
7 |
5.01 |
69 |
8 |
4.39 |
72 |
9 |
5.57 |
83 |
10 |
5.03 |
79 |
11 |
1.24 |
51 |
12 |
6.89 |
96 |
13 |
6.91 |
85 |
14 |
2.03 |
48 |
15 |
2.12 |
64 |
16 |
8.72 |
110 |
17 |
5.1 |
76 |
18 |
0.54 |
59 |
19 |
8.15 |
91 |
20 |
3.08 |
71 |
21 |
4.39 |
65 |
22 |
4.67 |
78 |
23 |
6.29 |
96 |
24 |
4.7 |
70 |
25 |
4.55 |
84 |
26 |
3.96 |
63 |
27 |
7.66 |
83 |
28 |
4.25 |
77 |
29 |
4.55 |
74 |
30 |
3.09 |
75 |
31 |
7.66 |
94 |
32 |
9.31 |
86 |
33 |
6.25 |
84 |
34 |
3.05 |
65 |
35 |
6.42 |
83 |
36 |
4.02 |
78 |
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