Josh Pethel DA Lab 3

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Jan 9, 2024

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Lab 03 - D-Fuse Data Collection Report Josh Pethel Introduction I piloted a study to collect data about D-Fuse, more specifically the patterns behind who goes to D-Fuse (categorized by gender, athletic affiliation), how long they wait in line, if specific food takes longer, and if people decide to go to D-Fuse on their way in/way out of the Mitchell Center. While observing D-Fuse on a Tuesday afternoon, I found no obvious patterns other than ordering a smoothie increases wait times. Questions I proposed several specific questions to assess the patterns behind D-Fuse’s operations. My Questions: 1) Does ordering a smoothie have a significant impact on wait time? 2) Is there a correlation to certain times throughout the time when athletes or non-athletes go to D-Fuse? Data To answer these questions, I collected data containing columns for the time a person entered the line, the time a person left the line, the total time a person spent in line, the gender, if a person had an obvious athletic affiliation (given by if they had a team backpack, were wearing team apparel, or clearly had equipment for a certain sport like lacrosse or football) . In my dataset each row represented a specific person’s visit to D-Fuse. I chose to collect data in this way because I was able to input it quickly into excel while observing the subject’s order, and their behavior before and after entering the D-Fuse line. DFuse.csv Column Name Variable Definition Units Data Type Variable Codes and definitions Missing value codes Time Entered Line The variable represents what time the person entered the D- Fuse line Hours and minutes Quantitative Integers N/A No missing data Time Exited Line The variable represents what time the person received their Hours and minutes Quantitative Integers N/A No missing data
food and exited the line Time Spent in Line The variable represents how long it took for the person to exit the line after entering the line Minutes (no wait was hours long) Quantitative Integers N/A No missing data Athletic Affiliation The variable represents if the person is assumed to have an athletic affiliation (judged by a team backpack, team apparel, or holding equipment clearly associated with a certain sport. N/A Qualitative and nominal Yes (Y) and N (No) No missing data Gender The variable represents what assumed sex the person embodies. N/A Qualitative and nominal Male (M) and Female (F) No missing data Just entered building? The variable represents if the person entered the Mitchell Center and immediately headed to D-Fuse N/A Qualitative and nominal Yes (Y) and N (No) No missing data Exited building afterward? The variable represents if the person immediately exited the Mitchell Center after receiving their food from D-Fuse N/A Qualitative and nominal Yes (Y) and N (No) No missing data Smoothie? The variable represents if the person purchased and received a smoothie from D- Fuse. N/A Qualitative and nominal Yes (Y) and N (No) No missing data Other food? The variable represents if the N/A Qualitative and nominal Yes (Y) and N (No) No missing data
person purchased and received food/drink other than a smoothie from D-Fuse. Analysis I conducted my analysis of the D-Fuse data using RStudio. 1) The summary for the two different categories separated by the question; was a smoothie ordered? Is pretty telling when looking at the summary with respect to wait times. The entire IQR and the mean for the “no smoothie” category is between 1 and 2 minutes, whereas the minimum value for the “smoothie” category is 2 minutes, and the IQR is between 4 and 6 minutes, showing a clear difference in wait times dictated by ordering a smoothie. Therefore, the summary statistics clearly show the difference between wait times due to ordering or not ordering a smoothie. 2) When examining the median and means for entry time for athletic affiliation (or lack thereof), the values are similar, as the medians are 4:32.5 (athletic affiliation) and 4:35.5 (none), and the means are even tighter at 4:31.9 (athletic affiliation) and 4:32.5 (none). However, the means and medians hint that there may not be a specific correlation, as both of them are close to 4:30, which is the median value for the study’s range of time (between 4 and 5 pm). The 1st and 3rd quartiles are within two minutes of each other, further proving that the summary statistics suggest no correlation between athletic affiliation and entry time.
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