Data Collection and Analysis- Average Commute Time to Work

Data Collection and Analysis- Average Commute Time to Work

Collect Data

For this assignment, I surveyed 25 drivers to find out the average number of minutes it takes them to drive to their workplace. Participants were individuals from different categories, including varied job positions, age groups, and locations. I decided to collect the data through the use of an online survey form, which I later distributed to the people via mail message and on the social media platforms they use. They include my friends, family members, colleagues, and acquaintances. Besides, such research helped me address a large number of individuals and gather the required information spontaneously.

Convenience sampling was employed when selecting the population group, as I had access to individuals within my immediate network who were easily available, keen, and willing to participate in the survey. This method made the data collection easier, which was a positive thing, though it had disadvantages. Firstly, the convenience sample may introduce bias and limit the representativeness of the sample (Emerson, 2021).

One notable issue I encountered during the data collection process was the potential for response bias. The sample participants of my survey would possibly have similar commuting patterns or live in the same type of neighborhoods, which could affect data skewing. For instance, people residing in the same locality may have almost similar traveling time every day, meaning that it could alter the overall distribution of the data. In order to minimize this issue, I attempted to reach out to a wide range of individuals from different backgrounds and living situations. Nevertheless, it is important to note that the convenience sampling method by design is biased; therefore, care needs to be taken while interpreting or generalizing any findings. Notwithstanding possible limitations, information collected from the 25 respondents who participated in the survey has provided valuable insights into commuting patterns and driving time in my network. Thus, the analysis began by using these replies and investigating further into our research query.

Organize Data

Present Data

In order to effectively summarize the collected data on commuting times, I decided to use a clustered column chart. This type of graph allows for a clear visualization of the distribution of drive times across different categories or groups, making it easier to identify patterns and compare the data.

Several reasons led to the choice of a clustered column chart for the data. Firstly, it gives a clear picture of how many people are within each commuting time category in terms of frequency or counts. In this format, it is easy to determine any clustering or concentration of the data which might provide some insights into typical commuting durations. Moreover, the clustered column chart is appropriate for comparing commuting times between groups (Dalmaijer et al., 2022). When columns are grouped together, it is easy to compare the commuting patterns among these sets. Additionally, its vertical orientation makes it visually appealing and intuitive for understanding numerical information where each bar height represents a corresponding value or frequency. Consequently, this is why the clustered column chart effectively communicates the distribution and comparative characteristics of travel time data; hence, it suits this study very well.

Summarize Data

The descriptive analysis of the commute times for 25 individuals yields the following statistical measures:

Mean

The mean is (39) minutes. This value represents the average time it takes for the surveyed individuals to drive one way to work.

Median

The median is (40) minutes. This is the middle value of the dataset when ordered from least to greatest, indicating that half of the individuals have commute times less than or equal to (40) minutes.

Mode

The mode is (25) minutes. This is the most frequently occurring commute time in the dataset, suggesting that a significant number of individuals have a (25)-minute commute.

Standard Deviation

The standard deviation is approximately (13.15) minutes. This measure reflects the amount of variation or dispersion from the mean. A higher standard deviation usually means that the commute times vary widely from the average (McGrath et al., 2020). Nonetheless, these statistics give a complete view of the commuting time data, emphasizing central tendency, dispersion, and shape of the distribution. The mean and median are almost the same, implying that there is a near symmetry in the distribution of data around the central values. The mode shows some possibility of clustering at the lower end of the range. There are significant disparities in terms of how long people take to commute as shown by the standard deviation and range. Skewness and kurtosis of the data give additional information concerning how far away from normality this shape is. All in all, these measures help understand how the individuals who were surveyed on the amount of time they take to work display a commuting pattern.

References

Dalmaijer, E. S., Nord, C. L., & Astle, D. E. (2022). Statistical power for cluster analysis. BMC Bioinformatics, 23(1). https://doi.org/10.1186/s12859-022-04675-1

Emerson, R. W. (2021). Convenience sampling revisited: Embracing its limitations through thoughtful study design. Journal of Visual Impairment & Blindness, 115(1), 76–77. https://doi.org/10.1177/0145482×20987707

McGrath, S., Zhao, X., Steele, R., Thombs, B. D., Benedetti, A., Levis, B., Riehm, K. E., Saadat, N., Levis, A. W., Azar, M., Rice, D. B., Sun, Y., Krishnan, A., He, C., Wu, Y., Bhandari, P. M., Neupane, D., Imran, M., Boruff, J., & Cuijpers, P. (2020). Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. Statistical Methods in Medical Research, 29(9), 2520–2537. https://doi.org/10.1177/0962280219889080

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Week 1 assignment
The following assignment will allow you to master the process of collecting, organizing, presenting, and summarizing data.

1. Collect Data: (25 points)
a. Survey at least 20 individuals to find out the number of minutes (on average) that they drive one way to work.
b. First, decide on how you will collect your data.
c. Describe the sampling technique used and how you made your decision on the method chosen.
d. Discuss any issues that occurred while obtaining the data.

Data Collection and Analysis- Average Commute Time to Work

2. Organize Data: (25 points)
a. Place the data in a table.
b. Decide the best way to organize with column or row headings.

3. Present Data: (25 points)
a. Decide on the type of graph that would be best to summarize the data.
b. Create the graph and be sure to label the appropriate area of the graph along with a title.
c. Explain the reasons that you chose the particular graph.

4. Summarize Data: (25 points)
a. Find the mean, median, mode, and standard deviation of the data.
b. Explain what each of these represents in terms of the data.