Tag: sk8

For my data viz charts, I tracked the relationship between my overall stress level from 1(no stress) to 10(severe stress) and five essential factors of my daily life(socializing, creativity, sleeping, exercising, and studying. I calculated these factors by how many percent of twenty four hours they take. 

I observed that stress is correlated with creativity(reading and writing) ina way that the more time I spend on creativity, the more stressed I am. I think that this is partly due to the fact that most of my creativity tasks are assigned by my Creative Writing First Year Seminar class, which brings a lot of stress for me. More studying time, which indicates upcoming exams, also contributes to increased stress. 

More socializing seems to lessen my stress level. For example, when my sociali time increases toward the end of the week and during the weekend, my stress level seems to decrease. 

Surprisingly, exercising does not seem to decrease stress for me. On Mondays and Wednesdays, during which I spend the most time exercising, I feel relatively more stressed. 

For the data viz charts, I tracked my overall stress level out of 10 for the day, my top 5 music artists for the day, and what I was reading that day. Overall, I wanted to see the correlation between what I consumed creatively compared to my stress levels.

I noticed that certain genres of music correlated to my stress levels of the day. I was listening to a lot of Kendrick Lamar and Jasiah leading up to my chemistry midterm. It made sense that I listened to Rachmaninoff, Berlioz, and Shostakovich leading up to my orchestra concert on 10/29/2023 as we played Rachmaninoff’s Symphonic Dances, Berlioz’s Roman Carnival Overture, and Shostakovich’s Piano Concerto No. 1.

For reading, the most notable difference was that the days I was less stressed, I read my current (re)read, ‘The Master and Margarita’ by Mikhail Bulgakov. As it got closer to the concert date, my stress levels increased as well as the percentage of my time spent reading music. I really like the graphs, mainly because of the pretty colors and how organized everything looks.

The peaks in stress were definitely associated with major events that I had going on in the past two weeks, so that was interesting to see. I would keep doing what I am doing if I continued to do this project but maybe make the excel sheet a bit more streamlined, so I didn’t have to keep creating new series and data points. I really like working with excel spreadsheets, and I didn’t realize that it could be so useful in self-analysis as well.

Throughout my whole life, I have been most inclined to think about life from a scientific and mathematical point of view. So, I was excited to hear that I would essentially be able to run an experiment on myself for the next two weeks. I decided to split the data points that I would be collecting throughout the week pretty evenly between categorical and numerical with the intent to use them to analyze each other. My main goal was to single out some things in my life that I believe make me a better overall person (working out, reading my bible, etc.) and compare them with different evaluators of my mood (happiness, anxiety, etc.). I assumed that these things that I have always strived to do daily improve my mood and overall well-being, but I wanted to put that up to the test in this study.
My first area of visualization includes five simple graphs showing fluctuations in my numerical evaluators of mood throughout the week. It was interesting to look back at some big things that happened in my life during these two weeks and see how my mood was during that time. For example, my parents came to visit during homecoming weekend which is represented just before halfway through these graphs. It is very clear that my happiness peaked during this time and my anxiety bottomed out. The next four areas of visualization were what I was most looking forward to examining when I began this study. As expected, talking with others and taking time for self-care had a positive outcome in many different categories throughout these two weeks. A friendly conversation with someone in the class had the largest statistical impact on my mood, dropping my discouragement level by about .5 on average. Surprisingly, there was no correlation displayed between the number of people I ate with at a meal and my anxiety levels during a certain part of the day.
Looking back at the way I conducted this study, I think it is interesting that my happiness levels were on average a 6-7. I consider myself a usually happy and “glass-full” person, but one thing I realized from this study is that there are still many levels to my happiness. During the normal times this week when I was thoughtlessly going through life, I would put a 5-7 for happiness even though I was still happy. In my mind, there was nothing that was going on that deserved an 8-10 at the time. But during the few times when something bigger happened, like my parents coming to town, I decided it was deserving of a higher rating. Essentially, I feel as though I was more than a ~6.3 happy over the past two weeks, but at the same time I feel that I rated myself pretty accurately which is very interesting to me. This introspective study was one that I enjoyed analyzing and I could see myself doing something similar in the future.

The main question I wanted to answer was whether if there was a correlation between my sleepiness and stress level. Throughout the two weeks, I gave myself a level from 1 to 10 for both my sleepiness and stress level each hour.

From the first two graphs, which each represent my sleepiness and stress level, I could not find a clear trend since the data was not organized. Thus, I created a graph that averaged the numbers I placed each day. From the third graph, there isn’t a clear correlation between my sleepiness and stress level, but the numbers slowly become similar in the afternoon and later the day. I chose to visualize my raw data using line graphs because I wanted to find trends, and since I recorded my data every hour, it would make sense to keep the data consecutive. For the third graph, I decided to use a bar graph because I wanted to compare the two numbers, and a bar graph shows a comparison most clearly.

During the data gathering, I initially had trouble determining the right number that represents my current state of sleepiness and stress. However, I did realize that there was no proper way since I am the only person who knows these feelings about myself. I trusted my instincts and just wrote the number in my mind. Also, there were times when I took a nap in the middle of the day. I decided to exclude these hours as it would not be reasonable to make sleepiness and stress values while being asleep.

From the results of my data, I realized that my stress levels grow with my sleepiness, with the exclusion of mornings. I have always known that I am not a morning person, so it was not surprising that I feel very sleepy in the morning. However, I did not expect my stress levels to increase with my sleepiness. I believe this may be because I know my productivity throughout the day, so when I feel sleepy on a time I should not be, I would feel obliged to work, causing stress. If I were to continue this project, I would include another variable: how long I am focused. I believe sleepiness and stress level are complete opposite variables that affect my ability to focus, so it would be interesting to test the relationships of these variables.

The question that I wanted to answer was how content I am with my life, and I measured “contentness” by utilizing five different categories: social life, productivity, outside time, inside time, and creativity. I chose to track those categories every other hour, only filling in the category that I indulged in the most for that specific hour. At the end of each day I reflected on how I felt, giving the day a number from one through five. Based on those numbers, I was able to conclude that my “contentness” is mostly dependent on how much I have socialized that day. On days where I rated the day a one or two, the amount of time I spent inside was measured the most. While gathering and evaluating the data, I had to consider other external factors such as developing a sickness towards the end of week one, which definitely impacted how accurate my data could’ve been for trying to measure how content I feel in life. I chose to visualize my data by using a colored bar graph, because I think that it’s easy to understand and interpret. These visualizations tell me that I feel most content and fulfilled when I hang out and socialize with friends and people, which is surprising because I consider myself a huge homebody, and that I get energy/appreciate my time spent alone. If I were to continue this project in the future, I would narrow the categories down to one in order to get more thorough results where I’m able to focus on one aspect of my life. I found this to be a valuable tool for self analysis as I was able to visually see a correlation between the feeling of fulfillment and my everyday activities.

I decided to track how sore I was on a scale of 1-10 every day. With basketball season beginning, I wanted to see how sore I was on each day, and how it related to how much I played and how much sleep I was getting. How does my daily routine regarding sleep and physical activity impact my body? Throughout the collection of my data, I realized that the earlier I woke up, the more sore I was. In addition to this, the more basketball I played, the more sore I was the next day. I also kept track of where I was sore, which was interesting to see the variation.

I decided to do a calendar format in order to represent each individual day. I included the date, what time I woke up, and how many hours of physical activity I had that day. I decided to use a front and back outline of a human body, in order to visually represent where I was sore. I included the rating out of ten, and each number represented a different color depending on the intensity of soreness. The lower levels of soreness were green, while the higher levels of soreness were red. While collecting my data, sometimes it was hard for me to decide on a set number out of ten. Some days, my calves would be hurting 8/10, but the rest of my body was only a 4/10. These days were difficult for me to decide on a set number, but I usually took the average. If I were to continue the project, I would probably use the same format, however I might shade in the whole human body and do different colors for different body parts depending upon my level of soreness.

file:///Users/carolineconnelly/Downloads/Sketch%208.pdf

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.