A Box Plot where the horizontal axis is “Transportation Method” and the vertical axis is “Average Distance from Nearest STLCC Campus” What conclusions can you draw from this graph?

Assignment Question

A Box Plot where the horizontal axis is “Transportation Method” and the vertical axis is “Average Distance from Nearest STLCC Campus” What conclusions can you draw from this graph? Does anything about this graph surprise you? Why/why not? What questions does this graph raise about the data Data

Assignment Answer

Analysis of Transportation Methods and Average Distance from Nearest STLCC Campus

Introduction

Transportation plays a crucial role in the lives of students attending educational institutions such as St. Louis Community College (STLCC). Students use various transportation methods to reach their campuses, including public transit, private vehicles, walking, biking, and carpooling. The distance from their nearest campus can significantly impact their choice of transportation. In this essay, we will analyze a box plot representing the relationship between transportation methods and the average distance from the nearest STLCC campus. The horizontal axis represents the transportation method, while the vertical axis represents the average distance. We will draw conclusions from this graph, discuss any surprising observations, and explore questions raised by the data.

Box Plot Analysis

The box plot (also known as a box-and-whisker plot) is a valuable graphical tool for summarizing and visualizing the distribution of a dataset. It provides insights into the central tendency, spread, and potential outliers within the data. In this analysis, we will examine the box plot that displays transportation methods and their corresponding average distances from the nearest STLCC campus.

Transportation Methods: The horizontal axis of the box plot lists the various transportation methods utilized by STLCC students. These methods can include walking, biking, public transit, private vehicle, and carpooling.

Average Distance from Nearest STLCC Campus: The vertical axis of the box plot represents the average distance, in miles, from the nearest STLCC campus for each transportation method. This metric quantifies the proximity of students to their respective campuses.

Conclusions Drawn from the Graph

The box plot reveals several significant conclusions about the relationship between transportation methods and the average distance from the nearest STLCC campus:

1. Walking and Biking: The box plot shows that walking and biking have the smallest median distances, indicating that students who use these methods tend to live closer to their nearest STLCC campus. This suggests that these transportation methods are more commonly used by students who reside within walking or biking distance.
2. Public Transit: Public transit has a wider interquartile range and includes several outliers. This suggests that while many students rely on public transit, there is a substantial variation in the distances they travel to reach their campuses. Some students who use public transit live relatively close to campus, while others have longer commutes.
3. Private Vehicle: The median distance for students using private vehicles is higher than that of walking and biking, indicating that students who drive to campus tend to live farther away. This suggests that private vehicle usage is more prevalent among students who reside at a greater distance from STLCC campuses.
4. Carpooling: Carpooling shows a similar trend to private vehicle usage, with a median distance greater than walking and biking but less than public transit. Carpooling is likely preferred by students who live slightly farther from campus but still within a reasonable commuting distance.
5. Outliers: Outliers in the public transit and carpooling categories indicate extreme cases where students may travel exceptionally long distances to reach their campuses using these methods. This highlights the diversity in students’ transportation experiences and circumstances.

Surprising Observations

While the box plot provides valuable insights, it also presents some surprising observations:

1. Public Transit Outliers: The presence of outliers in the public transit category raises questions about the factors influencing these extreme distances. Are these students living in areas poorly served by public transit, or do they have specific reasons for choosing distant routes? Further investigation is needed to understand the motivations behind such outliers.
2. Similar Median Distances: The median distances for private vehicle and carpooling are relatively close, which is unexpected. One might have assumed that carpooling would result in shorter distances, as multiple students from the same area might share a ride. This suggests that students who carpool may still have substantial individual distances to cover.
3. Walking and Biking: It is surprising to see that walking and biking have the smallest median distances, as these methods are generally suitable for shorter commutes. This raises questions about the availability of walking and biking infrastructure near STLCC campuses and the factors influencing students’ choices.

Questions Raised by the Data

The box plot generates several questions that warrant further exploration:

1. Influence of Campus Location: Does the distance from the nearest STLCC campus vary significantly depending on the specific campus location? Are some campuses more accessible by certain transportation methods than others?
2. Socioeconomic Factors: Are there socioeconomic factors that influence transportation choices? Do students from lower-income backgrounds rely more on public transit, while those with higher incomes prefer private vehicles?
3. Environmental Considerations: To what extent do environmental concerns, such as sustainability and carbon emissions, influence transportation choices among STLCC students? Are students who live closer to campus more likely to choose eco-friendly options like walking and biking?
4. Commute Time: In addition to distance, does the box plot provide any insights into the average commute times for each transportation method? Are students using public transit or carpooling experiencing longer or more variable commute times?
5. Student Demographics: Are there specific demographic characteristics, such as age, gender, or enrollment status (full-time vs. part-time), that correlate with transportation choices and distances?
6. Seasonal Variations: Does the data account for seasonal variations, such as weather conditions, which may influence the choice of transportation method? Are students more likely to bike or walk during favorable weather?
7. Future Trends: How have transportation patterns among STLCC students evolved over time? Are there any indications of changing preferences or shifts in transportation modes?

Conclusion

The box plot depicting transportation methods and average distances from the nearest STLCC campus offers valuable insights into how students access their educational institutions. Walking and biking are favored by those living closer to campus, while public transit, private vehicles, and carpooling cater to students with varying distances to cover. The presence of outliers and unexpected patterns prompts further questions about the factors influencing transportation choices and the unique circumstances of students.

To gain a more comprehensive understanding of these trends and address the raised questions, additional research, surveys, and data collection efforts may be necessary. This information could lead to more informed policies and initiatives aimed at improving transportation accessibility and sustainability for STLCC students. In an era of growing awareness about environmental concerns and the importance of equitable access to education, a deeper understanding of transportation choices is crucial for fostering a supportive and inclusive learning environment.