Predicting Smoking Rates in the U.S. Using Multiple Regression

Predicting Smoking Rates in the U.S. Using Multiple Regression

Presenter(s)

Marie K Bertolo

Description

In this work, we will try to predict the smoking rates (dependent variable) based on several independent variables (regressors) such as graduation rate rate (measured by high school graduation rates), race, religious status, age, median household income, crime rates and cigarette tax per pack. We also test if the smoking rate is dependent on the state. In the model, smoking rates are shown as a percentage of a state’s population and all 50 states are included to give an accurate representation of the United States as a whole. The data used was obtained from several websites such as Americas Health Rankings, the US census, the Kaiser Family Foundation, Governing and the Federal Bureau of Investigation. These variables are being tested to speculate the reasons behind the differences in smoking rates across U.S. states and to predict potential future rates.

Publication Date

4-5-2017

Project Designation

Capstone Project - Undergraduate

Primary Advisor

Maher B. Qumsiyeh

Primary Advisor's Department

Mathematics

Keywords

Stander Symposium project

Predicting Smoking Rates in the U.S. Using Multiple Regression

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