Logistic regression is a powerful tool I chose to analyze the probability of shipment delays in my warehouse shipping data. # I noticed that a linear regression model would struggle with predicting probabilities since it can produce values outside the [0, 1] range. # To address this, I applied logistic regression to ensure meaningful and interpretable predictions. # Step 1: Generate the dataset # I created a simulated dataset that represents shipment volumes and whether they were delayed (Delayed = Yes). # This allows me to explore how shipment volume impacts delay probability.

DVF

A bar chart illustrating purchase count by state, showing regional differences in demand

Customer reviews from "Poor" to "Excellent."

Highlighted the most popular books in the dataset, helping identify potential bestsellers.

Compared high-rated vs. low-rated books to see how reviews impact purchases.

Log returns