Presentation Abstract

This presentation seeks to give the audience a better outlook on the ways in which data science methods are used to assess Malnutrition in Ethiopia. The presentation begins by giving an overall assessment of the malnutrition problem in Ethiopia, providing statistical evidence to support. The presentation then follows up with an assessment of two data science methods that have been used in researched study to either collect or analyze data. The first is an assessment of logistic regression, a data analysis method that is frequently used to organize data and develop function curves. The second is an assessment of an unconventional electronic search data collection method that is used in a research study that draws its data for Ethiopian malnutrition from previously studied data sets. The presentation ends with a research gap, followed by a brief introduction to a potential research plan that can be used to fill in the research gap.