An Example Of A Report Date To From R E Analysis Of Buena Sc ✓ Solved

An Example Of A Report Date To From R E Analysis Of Buena School

Per your request, I have prepared an analysis of the Buena School District Bus Data with respect to the maintenance cost for last month. The following questions will be answered throughout the report:

• Around what values do the data tend to cluster?
• What was the mean maintenance cost last month?
• What was the median cost?
• Is one measure more representative of the typical cost than the other?
• What is the range of the maintenance costs?
• What is the standard deviation (i.e., the variation or spread in the data)?
• About 95 percent of the maintenance costs are between what two values?

Last month, the Buena School District provided maintenance on 80 vehicles, which totaled $36,023.00. The maintenance was for passenger vehicles that ranged from 6 passengers to 55 passengers in size and had been in use from 1 to 14 years. The miles traveled by the vehicles ranged from 700 to 1,000 miles, and each vehicle used either gasoline or diesel fuel. The purpose of this report is to analyze the maintenance cost for the last month. The results of the analysis follow:

• The data tend to cluster around the $400 range.
• The mean of the data is $450, and the median of the data is $456.
• The median of the data appears to be more representative of the typical cost than the mean due to the fact that the data are not symmetrical when plotted.
• The range of maintenance costs is $241, since the smallest cost is $329 and the largest cost is $570.
• The variation or spread in the data is $53.68.
• About 95% of the maintenance costs are between $438 and $462.

The output on which this report is based is found in the Appendix. If additional information or clarification is needed, please feel free to contact me.

Paper For Above Instructions

The analysis of the maintenance costs for the Buena School District provides valuable insights into the vehicular maintenance expenditures for the previous month. By examining the data meticulously, we can derive various statistics that not only depict the maintenance costs but also enable a comparative understanding of the values.

To initiate the analysis, we first assess how the data clusters. The findings indicate that the data tends to cluster around the $400 mark. This clustering signifies a concentration of maintenance costs around this value, providing an initial reference point for assessing overall vehicle maintenance expenses.

Next, we look into the calculation of the mean and median maintenance costs. The mean maintenance cost is calculated at $450, while the median stands at $456. The mean offers a general average of maintenance costs but can be skewed by extreme values. In contrast, the median, being the middle value in the data set when sorted, presents a more accurate representation when the data distribution is non-symmetrical. Given that the costs are likely influenced by outliers, the median serves as a more reliable indicator of typical maintenance cost.

When investigating the representative nature of the mean versus the median, we recognize that the median is a more robust measure in this context. The presence of data asymmetry suggests that extreme high or low costs could distort the mean, thereby making the median a more appropriate measure of typical maintenance costs.

The range of maintenance costs, determined to be $241, oscillates between the smallest cost of $329 and the largest cost of $570. This range effectively highlights the spread of values within the data set, indicating the variability in maintenance expenses across different vehicles. Consequently, the spread of the data is further emphasized by the standard deviation, calculated at $53.68. The standard deviation quantifies how much the individual maintenance costs deviate from the mean cost. A lower standard deviation signifies that the maintenance costs are closely clustered around the mean, whereas a higher standard deviation would indicate a wider variability.

An essential aspect of understanding maintenance costs is the identification of the confidence interval that incorporates 95% of the maintenance costs. Our analysis reveals that approximately 95% of the maintenance costs are confined within the range of $438 to $462. This range is crucial for budget forecasting and cost management within the district, as it allows for a better understanding of anticipated maintenance expenditures.

The statistics provided in this analysis offer a clear view of the maintenance costs incurred by the Buena School District for their fleet of vehicles. The report emphasizes the relevance of calculating descriptive statistics like the mean, median, standard deviation, and range, which ultimately guide financial decision-making and resource allocation for maintenance tasks.

If further analysis is desired, such as examining additional variables influencing maintenance costs or the circumstance surrounding specific high-cost maintenance instances, it is recommended to gather more data. Future steps may include evaluating the relationship between vehicle age, type, usage, and incurred maintenance costs over a longitudinal study.

In conclusion, the analysis of the maintenance costs for the Buena School District sheds light on important fiscal aspects of vehicle upkeep. By leveraging statistical measures, we can make informed decisions that align with budgetary constraints and operational efficiency. For any additional queries or detailed examination of the statistical outputs, I remain available for further communications.

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