a. (*) Calculate p. b. (**) Set up a p chart to track the proportion of late arriv- als. (Note: Each sample consists of 30 observations.) c. (***) Airline travel is characterized by busy and slow seasons. As a result, what is "normal" during one time of the year wouldn't be “normal” at some other time. What difficulties might arise as a result of using a single control chart to track the propor- tion of late arrivals? What could Central Airlines do about this?

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a. (*) Calculate \( \bar{p} \).

b. (**) Set up a \( p \) chart to track the proportion of late arrivals. (*Note: Each sample consists of 30 observations.*)

c. (***) Airline travel is characterized by busy and slow seasons. As a result, what is "normal" during one time of the year wouldn’t be "normal" at some other time. What difficulties might arise as a result of using a single control chart to track the proportion of late arrivals? What could Central Airlines do about this?
Transcribed Image Text:a. (*) Calculate \( \bar{p} \). b. (**) Set up a \( p \) chart to track the proportion of late arrivals. (*Note: Each sample consists of 30 observations.*) c. (***) Airline travel is characterized by busy and slow seasons. As a result, what is "normal" during one time of the year wouldn’t be "normal" at some other time. What difficulties might arise as a result of using a single control chart to track the proportion of late arrivals? What could Central Airlines do about this?
**Monitoring On-Time Arrival Performance at Central Airlines**

Central Airlines aimed to assess its on-time arrival performance by creating a control chart. Over a 10-day period, the airline randomly selected 30 flights each day and monitored the number of flights that arrived late. Below are the results of this data collection:

| DAY | SAMPLE SIZE | NUMBER OF LATE-ARRIVING FLIGHTS |
|-----|-------------|---------------------------------|
| 1   | 30          | 2                               |
| 2   | 30          | 3                               |
| 3   | 30          | 4                               |
| 4   | 30          | 0                               |
| 5   | 30          | 1                               |
| 6   | 30          | 6                               |
| 7   | 30          | 4                               |
| 8   | 30          | 2                               |
| 9   | 30          | 3                               |
| 10  | 30          | 5                               |

The table illustrates the consistency and variability in the number of late arrivals across the ten days sampled. These results could be used to identify potential areas for improvement in the airline's scheduling and operations procedures.
Transcribed Image Text:**Monitoring On-Time Arrival Performance at Central Airlines** Central Airlines aimed to assess its on-time arrival performance by creating a control chart. Over a 10-day period, the airline randomly selected 30 flights each day and monitored the number of flights that arrived late. Below are the results of this data collection: | DAY | SAMPLE SIZE | NUMBER OF LATE-ARRIVING FLIGHTS | |-----|-------------|---------------------------------| | 1 | 30 | 2 | | 2 | 30 | 3 | | 3 | 30 | 4 | | 4 | 30 | 0 | | 5 | 30 | 1 | | 6 | 30 | 6 | | 7 | 30 | 4 | | 8 | 30 | 2 | | 9 | 30 | 3 | | 10 | 30 | 5 | The table illustrates the consistency and variability in the number of late arrivals across the ten days sampled. These results could be used to identify potential areas for improvement in the airline's scheduling and operations procedures.
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We have to find

a.  Calculate p(bar) 

 

b. Set up a p chart to track the proportion of late arriv als. 

 

c.  Airline travel is characterized by busy and slow seasons. As a result, what is "normal" during one time of the year wouldn't be "normal" at some other time. What difficulties might arise as a result of using a single control chart to track the propor tion of late arrivals? What could Central Airlines do about this?

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