Statistical Analysis of Infant Mortality and Social Contributions

Overview

The purpose of this experiment is to determine the relationship of breastfeeding and other social and economic factors to infant mortality on the Louisiana and national level. The researcher hypothesized that breastfed ever data for both Louisiana and the United States would have the strongest inverse correlation with infant mortality. For this project, data for Louisiana and United States infant mortality, breastfed ever, breastfed for 6 months, breastfed for 12 months, average mother age at first birth, female high school graduation, median household income, and unemployment rate were gathered and compiled into tables. Then, the relationship between Louisiana and United States infant mortality and each other factor was analyzed by their R2 values. The R2 values showed that for Louisiana, median household income had the strongest negative correlation with infant mortality. For the United States, the R2 values showed that breastfed ever data had the strongest negative correlation with infant mortality. Therefore, the data failed to reject the null hypothesis since both the Louisiana and United States correlation between breastfed ever and infant mortality was not the strongest.

Competition history

• ISEF 2022 Computational Biology and Bioinformatics · Entry CBIO015 · Atlanta, Georgia, United States Affiliated fair in LA, United States of America

Resources

• ISEF abstract page ↗

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