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Waiting Times Cumulative frequency 70 60 50 40 30 20 10 10.5 15.5 20.5 25.5 30.5 35.5 40.5 45.5 Time

Waiting Times Cumulative frequency 70 60 50 40 30 20 10 10.5 15.5 20.5 25.5 30.5 35.5 40.5 45.5 Time

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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*NOTE** Please see picture of graph attached. 

 

Waiting Times The frequency distribution shows the waiting times (in minutes) for 48 patients at a walk-in medical facility. Construct an ogive for the data.

 

 

Class Limits Frequency
11-15
6
16-20
8
21-25
15
26-30
9
31-35
5
36-40
3
41-45
2
Total
48
### Waiting Times Analysis #### Overview The graph displayed above represents the cumulative frequency of a set of waiting times recorded for a given scenario. The X-axis (horizontal axis) shows the waiting times in increments of 5 units, ranging from 10.5 to 45.5 units of time. The Y-axis (vertical axis) displays the cumulative frequency, ranging from 0 to 70. #### Details - **Title**: Waiting Times - **Y-axis**: Cumulative frequency - **X-axis**: Time #### Data Points - For each time interval on the X-axis, the associated cumulative frequency is labeled. All the cumulative frequencies recorded for the corresponding times (10.5, 15.5, 20.5, 25.5, 30.5, 35.5, 40.5, 45.5) are 0. - Each data point on the graph is represented by a blue dot at the intersection of the corresponding time interval on the X-axis and the cumulative frequency on the Y-axis. #### Observations - All the cumulative frequencies at the given time intervals are 0. - This indicates that there were no instances in which the waiting time fell into any of the recorded intervals. #### Conclusion The data suggests there were no waiting instances recorded for the displayed time intervals. Users should ensure data collection methods are correctly implemented to provide meaningful insights into the waiting time analysis. Be sure to validate data inputs and examine any potential issues with the collection process if results are unexpected or inconsistent. #### Further Actions To gain more accurate insights, it is recommended to: 1. Review the data collection process. 2. Ensure there were no errors in data entry. 3. Conduct a repeat study if necessary, ensuring all parameters are correctly monitored and recorded. #### Additional Notes - The graph can be useful to display trends when there are variations in the data. - Changes in cumulative frequencies can indicate patterns over time, which are essential for making informed decisions. For more information or to submit your analysis, click on the "Submit Assignment" button at the bottom right corner of the screen.
Transcribed Image Text:### Waiting Times Analysis #### Overview The graph displayed above represents the cumulative frequency of a set of waiting times recorded for a given scenario. The X-axis (horizontal axis) shows the waiting times in increments of 5 units, ranging from 10.5 to 45.5 units of time. The Y-axis (vertical axis) displays the cumulative frequency, ranging from 0 to 70. #### Details - **Title**: Waiting Times - **Y-axis**: Cumulative frequency - **X-axis**: Time #### Data Points - For each time interval on the X-axis, the associated cumulative frequency is labeled. All the cumulative frequencies recorded for the corresponding times (10.5, 15.5, 20.5, 25.5, 30.5, 35.5, 40.5, 45.5) are 0. - Each data point on the graph is represented by a blue dot at the intersection of the corresponding time interval on the X-axis and the cumulative frequency on the Y-axis. #### Observations - All the cumulative frequencies at the given time intervals are 0. - This indicates that there were no instances in which the waiting time fell into any of the recorded intervals. #### Conclusion The data suggests there were no waiting instances recorded for the displayed time intervals. Users should ensure data collection methods are correctly implemented to provide meaningful insights into the waiting time analysis. Be sure to validate data inputs and examine any potential issues with the collection process if results are unexpected or inconsistent. #### Further Actions To gain more accurate insights, it is recommended to: 1. Review the data collection process. 2. Ensure there were no errors in data entry. 3. Conduct a repeat study if necessary, ensuring all parameters are correctly monitored and recorded. #### Additional Notes - The graph can be useful to display trends when there are variations in the data. - Changes in cumulative frequencies can indicate patterns over time, which are essential for making informed decisions. For more information or to submit your analysis, click on the "Submit Assignment" button at the bottom right corner of the screen.
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