Category: Student Posts

The primary question I sought to answer was: how closely does my objective recording of factors contributing to happiness (such as exercise, sleep, diet, leisure, and social interaction) correlate with my subjective feelings of happiness on a day-to-day basis?

Drawing from the data, there’s a noticeable correlation between days with higher levels of exercise, satisfactory diets, and ample sleep with increased feelings of happiness. This suggests that physical well-being significantly influences emotional states. However, there are instances where even with adequate sleep and exercise, the happiness score is relatively low. This could be attributed to factors outside of the recorded parameters, perhaps work-related stress or personal issues. The decision to visualize this data using bar graphs was to offer a clear comparison between external factors and internal feelings on a day-to-day basis. The visual representation showcases the ebb and flow of happiness, emphasizing that it’s a culmination of various factors, some tangible and others intangible. In addition, the charts show a clear trend: the closer I get to the weekend, the higher the happiness index. That is because social interaction plays an important role in my happiness. I love to gain energy and get refreshed during the interaction with my friends.

If this project were to be continued, it might be beneficial to refine the categories. For instance, breaking down “leisure time” into specific activities could offer more precise insights into which leisure activities contribute most to happiness. Furthermore, tracking other variables like stress levels or external factors (like weather or significant events) could add more depth to the analysis. Data visualization proves to be a valuable tool for self-analysis for me . Visualizing personal data in this manner offers a unique perspective on one’s life and can be a guide for making informed decisions to enhance well-being. Nonetheless, this endeavor underscores the importance of holistic self-awareness and the intricate dance between our external actions and internal emotions.

For this assignment, I decided to track my hunger and energy levels throughout the day, hoping to answer the question “How does my hungriness affect my energy levels at different times of the day?” This was an area of interest for me because I find my energy and hunger frequently fluctuates throughout the day and I hope for both to be more consistent. I also wanted to track to see if there was any correlation between the two categories. I decided to track these categories at 4 different times of the day – 10:00 AM, 2:00 PM, 6:00 PM and 10:00 PM. The timing of when I eat influences the results, so I tracked my energy and hunger on a scale from 1-10 before I’ve eaten that day, after I eat lunch, before I eat dinner, and after I’m done eating for the day.

Once I finished my data collection, I tried to find patterns in the table but it was too difficult so I averaged the values and created a line graph. At first, I was hesitant to average because I knew there were differences from one day to another, but I knew it would help to see a larger general trend.

I realized immediately the correlation between my hunger and energy throughout the day. Both followed a similar pattern of ups and downs throughout the day. What surprised me was how clear the dip in both categories was at 2:00. I usually eat lunch around 1-1:30 so it makes sense that I’m not hungry afterwards, but my energy had the exact same pattern. I tend to skip eating breakfast in the mornings, so typically lunch is my first meal. Looking at the visual, it appears that eating my first meal of the day around noon causes me to feel tired and have low energy shortly after. At the same time, it’s hard to determine causality because there are several other factors. For example, I try to go on a run every day, which is typically in the afternoon. That would explain why I have much higher levels of energy and hunger around 6 since that’s after I’ve finished my run.

I was able to address the main question for this assignment by seeing a clear association between hunger and energy. Now that I can see my data clearly, however, I would make changes if I were to continue this project in the future. I couldn’t draw conclusions about causality because there are lots of variables that influence my energy, so I would include other categories like exercise and amount of sleep the night before, as well as separating the weekdays from the weekends. Still, this assignment was a useful tool for self analysis because I realized that maybe I wouldn’t feel so tired after I eat lunch if I began eating something in the morning, even if it is just a granola bar.

For this Sunday Sketch assignment, I decided to track two sets of contrasting categories: sleepiness vs. energy and stress vs. contentedness. Sleepiness and stress are the most prominent emotions I feel throughout any school week, so I was curious to see how they fluctuated on a daily basis.

As seen in my graph, I decided to use a line graph that would show the change from day to day over the course of the three-week frame where I took data every morning (I felt this was the best way to measure my sleepiness and pre-class stress levels). I noticed that the category that fluctuated the most was, unsurprisingly, my levels of stress. I noticed that it increases at the start of the week, where professors are assigning weekly assignments, and then decreases the closer I got to the weekend, showing how I was completing assignments and necessary assessments/projects. I noticed my stress levels were particularly higher on Fridays, which I believe to be connected to the number of assessments I have each Friday, which is at least two, one of them being my Computer Science course.

I found this to be a valuable tool for analyzing myself, and if I were to continue this process, I would likely gather my data using the same process that I have been using, it allows me to look at myself at the start of each day and encourages me to be the best version of myself so tomorrow’s numbers are healthier. I hope to be more aware of my levels of stress and sleepiness so I can take the necessary course(s) of action and be a more energetic and content person.

One of the conceptual issue that I was tracking was “How often do I feel stressed out throughout the week?” Lately, one of the emotions I’ve been feeling intensely is stress. Whether is about academics, social life, or personal issue, I feel stressed out about the tinites situation. Creating a data that visualizes how often i feel stressed showed me how my stress levels are at an unhealthy level. At the end of each day, I took note of how high my stress levels from that specific day was from a scale of 1-10. I found it easy to track my data on my notes app because I use it quite often for my everyday mini notes. If I were to continue this project, I would probably keep track the same way because it’s a habit to go on my notes app. Overall collecting data was a good tool for self reflection and it showed me areas in my life or habits that i need to fix to be better myself.

Another conceptual issue that I was tracking was “How many hours I devoted to myself throughout the week? My idea was to compare how my high stress levels are and what I do to take time for myself . One of my observations is the main cause of my stress was academics. Majority of the time, I choose to study for hours because it doesn’t feel right when i taking time for myself and not being productive. But the times I do take times for myself is usually sleeping and once in while socializing with my friends. Similar to the first data, I tracked it on my notes app as well. If I were to continue this project instead of tracking how many hours i take for myself, i would substitute some key activities to destress and see how i feel after the first week. Overall collecting both data showed me, how unhealthy my habits are and why I need to change my habits.

The activity that I decided to collect data on was the type of music I listen to when I am studying. I am a huge music fan and I constantly have my earbuds in listening to music, for almost every activity that I do during the day. During the time we had to collect data for this assignment, happened to overlap with my studying for the QTM midterm. So the data I decided to collect was does the type of music that I listen to when I study affect how well I stay engaged. Of course there are a lot of outside factors that could have also played a significant role in this study, so I tried to limit al of these factors by trying to got to sleep and wake up at the same time during these days and making sure I go to the gym after I study, to try to limit fatigue as a factor of my data. In addition, I went to the quiet section of the library, the Matheus Reading Room, to try to limit outside factors affecting my study as well.

The main way in which I measured my data was observing how many times i looked at my phone during my study session for my QTM midterm. I made this a sign of “losing focus” in my study. I studied for this midterm for 10 days, 5 days during the week of October 16th, and 5 days during the week of October 23rd. I listened to 5 different genres of music: Hip Hop, Country, R&B, White Noise and Hindi. I listed to each genre of music twice during the span of the two week period, to gather my data.

I also logged the time I spent studying for my for my QTM midterm each day, so I could see if this had any effect on my ability to focus as well.

The results demonstrate the the music that I actually study best with is R&B, but this was also the type of music that I spent the least amount of time studying to as well, but the result that surprised the most was that the “White Noise” genre of music was actually the type of music that caused me the least amount of focus, because this is considered to be the best type of music for most people to study and get the most work done with.