For the Markov assignment, I worked with Erin Hurley and Mahmoud Oraby. Before jumping into the code, I took the time to map things out and brainstorm how I would approach the project. I also watched all the guide videos provided, which really helped me understand the requirements and gave me more confidence moving forward. My overall strategy was to break the problem into smaller, manageable parts and build each component step by step, especially focusing on the generation logic. Erin had a similar mindset—she planned things out on paper first and prioritized a clear and logical structure, which helped keep us organized. Looking back, I think I would improve my approach by spending a bit more time upfront visualizing the data flow. That would probably help catch bugs earlier and reduce the need for major rewrites later. According to my classmates, my code followed the Google Java Style Guide fairly well, though there were a few small formatting issues. Erin and Mahmoud's code was also clean and aligned with the style guide standards.
This week, I learned more about probability distributions, density plots, histograms, and how to visualize data using Python libraries such as Pandas, Matplotlib, Seaborn, and SciPy. I practiced creating density plots, box plots, cumulative density plots, and histograms using real datasets. I also learned how changing things like bin width, bandwidth, transparency, and sample size can affect the appearance and interpretation of graphs. Another important topic was understanding skewness and how transformations such as log10 can help make heavily skewed data easier to analyze. One thing I found interesting was how probability density functions (PDFs) and histograms can represent the same data differently. Before this week, I thought graphs mostly showed the same information in different styles, but now I understand that each type of plot has a different purpose and can make patterns easier or harder to notice. I also learned that larger sample sizes tend to reflect the true distribution...
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