Please Help With My Homework I Do Not Understand It Thank Yo

Please Help With My Homework I Am Not Understanding It Thanks A Lot

Please help with my homework! I am not understanding it! Thanks a lot! Your supervisor has asked you to provide a visual representation of the following data. Florida Turnpike System - Road Ranger Calls. Consider different types of charts and graphs that would best depict the data. After creating a visual representation, provide a short summary of the data. Include any percentage of increase or decrease from year to year. Submit your completed assignment to the drop box below. Please check the Course Calendar for specific due dates. Save your assignment as a Microsoft Excel spreadsheet. The name of the file should be your first initial and last name, followed by an underscore and the name of the assignment, and an underscore and the date. An example is shown below: Jstudent_exampleproblem_101504

Paper For Above instruction

Introduction

The task involves creating an effective visual representation of data related to the Florida Turnpike System Road Ranger calls from the years 2013 and 2014. The goal is to select the most suitable type of chart or graph to illustrate the different categories of calls, analyze the changes between the two years, and provide a concise summary highlighting key trends and percentage variations. The data encompasses five categories of calls, each with numerical counts for the respective years.

Data Overview

Choosing the Appropriate Visual Representation

The data presents categorical comparisons across two years, with numerical counts for each category. A clustered bar chart would be ideal because it allows for easy visual comparison of each category between 2013 and 2014. The bar chart can distinctly display the fluctuations in call volumes, making it straightforward to identify increases or decreases for each category. Alternatively, a stacked bar chart could illustrate the combined total and the segmental changes, but for clear comparison across categories, the clustered bar chart is most effective.

Creating the Visual

Using Microsoft Excel, the data can be inputted into a spreadsheet with labels for each category and the two years. The chart is then generated by selecting the data range and inserting a clustered bar chart. Customizations such as different colors for each year, data labels, and a descriptive title enhance readability. The visual clearly shows the contrast between the two years for each call type and highlights shifts in the call patterns.

Data Analysis and Summary

The visual analysis reveals significant changes in the number of calls across the categories. Notably, calls for "No Assistance Required" increased from 22,091 in 2013 to 31,223 in 2014, representing a percentage increase of approximately 41.3% ((31,223 - 22,091) / 22,091 * 100). This suggests a rise in non-assistance calls or perhaps increased reporting or monitoring.

Conversely, calls for "Disabled / Stranded Motorist" remained relatively stable, decreasing slightly from 32,674 to 32,122, an insignificant change of about 1.7%. The categories related to maintenance and debris removal tell a different story: "Maintenance of Traffic During Accidents" saw a decline from 4,284 to 2,040, which is about a 52.3% decrease. This reduction could be indicative of fewer accidents requiring traffic maintenance or improved traffic management protocols.

The most prominent decrease is observed in "Debris Removal and Abandoned Vehicles," which dropped from 41,837 to 30,882, approximately a 26.2% decrease. This significant reduction may reflect improved roadside maintenance or increased efficiency in debris clearance services.

Overall, the data indicates a rise in non-assistance calls and a decline in accident-related and debris-removal calls, possibly reflecting changes in traffic conditions, incident rates, or operational strategies over the year.

Conclusion

The chosen visual, a clustered bar chart, effectively depicts the comparative data between 2013 and 2014 for each call category. The analysis highlights key trends, with substantial increases in some call types and decreases in others, providing valuable insights for traffic management and resource allocation. Presenting the data visually facilitates quick comprehension of complex information and supports informed decision-making.

References

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