Compute multiple types of correlations analysis (Pearson correlation, R^2 coefficient of linear regression, Cramer's V measure of association, Distance Correlation,The Maximal Information Coefficient, Uncertainty coefficient and Predictive Power Score) in large dataframes with mixed columns classes(integer, numeric, factor and character) in para…

R Shiny App to determine the factors that are most influential in patients’ survival of CHD. I created a Logistic Regression model in R using RStudio to predict the survival of CHD patients. Retrieved the data from the PHIS database using SQL & built tableau dashboards. The model predicted the survival of CHD with an AUC of over .90 and indicate…

Aims to build a classification model that can provide a basic understanding of what types of personal characteristics are likely to cause stroke and the probability that those characteristics lead to stroke.

Statistical Multivariate Regression Analysis to determine the effects of mortality, economic and social factors on life expectancy.

Identify the most important variables that contribute to the level of sustainability of schools using supervised machine learning. Use the importance to assign a weight to each characteristic and calculate a sustainability index for each school.

Functional specification to calculate per country's happiness score

Linear Regression to identify the important physicochemical properties of the substrate that influence the aerial biomass production in the Cape Fear Estuary.

R package for statistics of eigenvalue dispersion indices

Poster is available:

Useful graphs for financial projects