My presentation for the Shiny application I created as my final project in the Coursera Data Science Specialization.

For the Data Science Capstone project, a milestone report summarizing the work done to date in order to complete the final project is a required deliverable. This report contains information about the access, loading, and processing of the dataset under study for the project.

This ioslide deck provides information about the Shiny application developed for the final course project of the Developing Data Products session of the the Coursera Data Science Specialization.

This is a simple presentation using the plotly package to display a box plot of the number of phones used worldwide.

This is the second course project in the Developing Data Products session of the Coursera Data Science Specialization. It uses the plotly R library to create an interactive graph of the WorldPhones dataset available in R.

This is the first course project for the Developing Data Products session of the Coursera Data Science Specialization. It uses the Leaflet library and data from the Open Baltimore website to create an interactive map of Famer's Markets in the Baltimore City area.

This report describes how a prediction model was created and used to predict the labeling of exercises performed by six participants. It was created as the final course project for the Practical Machine Learning module of the Coursera Data Science Specialization

This is the work I submitted for the seventh course in the Data Science Specialization offered by Coursera. It attempts to use linear regression in an analysis of the mtcars dataset in order to answer the question of which transmission, automatic or manual, provides greater fuel economy.

This is my attempt at the first course project in the class Statistical Inference as part of the Coursera Data Science Specialization. It uses simulation to show how the Central Limit Theorem applies to the Exponential Distribution.

This is my attempt at the second course project for the Statistical Inference class in the Coursera Data Science Specialization. It uses the techniques of EDA and Hypothesis Testing to evaluate the effects of supplements in different dosages on the growth of Guinea Pig odontoblasts.

This publication is the result of work I did for my second peer assessment in the Coursera class Reproducible Research, which is the fifth course in the Data Science Specialization Track.

This is my first course project for the course "Reproducible Research" offered by Coursera.