We explores the relationship between sleep and various variables using the "sleep75" dataset. We begin by filtering the data to include only observations where individuals are in the labor force (to exclude children etc.). Then computes the correlations between sleep and other variables, visualizing them through a bar plot. Next, it focuses on the minutes worked per week and examines its relationship with sleep using a linear regression model. The notebook further investigates the relationship between sleep and the hourly wage. Another linear regression model is employed, and a scatter plot with the regression line is created. Overall, the notebook provides insights into the relationships between sleep, work-related factors, and wages. It combines correlation analysis, visualization, and linear regression modeling to examine these connections and offers a comprehensive understanding of the dataset.