This week, I learned how to connect a Java program to a MySQL database using JDBC. I practiced creating a connection, inserting new data, selecting records, and managing transactions with commit and rollback. I also learned how to handle SQL exceptions and make the program give clear error messages when something goes wrong, such as duplicate IDs or missing departments. Another important part was understanding how to add the MySQL connector JAR file or dependency in my project so the driver loads correctly. Overall, this week helped me understand how Java interacts with databases and how to make programs that safely read and write data.
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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