As part of the Coursera Data Science Specialization (Capstone Project), this text prediction application was developed using Natural Language Processing (NLP) techniques.

This document presents the results for the text analysis as part of the Coursera Data Science Specialization Capstone project.

Using data from the OECD Regional Well-Being iniciative, I created a Shiny App that allow you to compare 11 topics between two different countries (OCDE members).

Using the mtcars dataset in R, I present a plot (plotly) that includes all the relevant aspects one would consider when buying a car, such as the Miles Per Gallon (mpg), weight (wt), displacement (disp), transmission (am), number of cylinders (cyl), Horsepower (hp) and, of course, the brand and model of the car.

Show the LEAFLET library capacities using 10 Famous Trees of the World.

Exploring the ToothGrowth dataset in R and use hypothesis test to compare tooth growth in guinea pigs by supplement and dose.

For this part of the project we’re going to investigate the exponential distribution in R and compare it with the Central Limit Theorem. The Central Limit Theorem specifies that the means drawn from multiple samples will resemble the bell-shaped normal curve.

The aim of this analysis is to answer some questions regarding the health of the population and the economic consequences of severe weather events in the U.S. registered between 1950 and 2011.