Modeling Sleep Efficiency

This study explores how alcohol use, exercise, and smoking affect sleep quality by analyzing a dataset containing various lifestyle and sleep-related factors. Using a regression-based predictive model, the research identifies relationships between these behaviors and sleep outcomes, with the final linear regression model achieving a mean absolute error of 0.051.

I’ve always been interested in sleep and why some people tend to sleep better than others. I think it’s important to recognize what could be affecting a person’s sleep and what they can do to improve it. The goal of my research question, “How much do alcohol, exercise, and smoking affect sleep?” is to show how factors such as these can affect the quality of one’s sleep. I found a data set consisting of many factors that can affect sleep, as well as sleep quality. Using this data set, I built a model that allows you to input values for factors and come out with a sleep quality score. My model is a regression model, as it makes predictions through numerical data given to it. I tested out different models, settling on the most accurate one, Linear Regression, with a mean absolute error of 0.051.

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Research Paper