This ia a presentation on the capstone project from the Coursera Data Science Specialization Course from the Johns Hopkins University

This is an exploratory analysis on the data sets in order to create a corpus for the Word prediction web app that will be created on a Shiny server in R for the capstone project of Data Science Course from JHU on Coursera.

Explaining reactivity in Shiny with plotly, for presentation purpose of the Shiny web app

an R Markdown Presentation created with ioslides and plot with Plotly embedded for purpose of Developing Data Products assignment on Coursera.

Map with some markers and custom icons , created as a project for Coursera assignment. Keep researching .

basic scatter plots and 3D color plots

“gvis + ChartType” Motion charts: gvisMotionChart Interactive maps: gvisGeoChart Interactive tables: gvisTable Line charts: gvisLineChart Bar charts: gvisColumnChart Tree maps: gvisTreeMap

Automatic transmission vs Manual transmission

Using devices such as Jawbone Up, Nike FuelBand, and Fitbit it is now possible to collect a large amount of data about personal activity relatively inexpensively. These type of devices are part of the quantified self movement – a group of enthusiasts who take measurements about themselves regularly to improve their health, to find patterns in their behavior

Training and test sets from Spam data, using the caret package

A correlation between corruption and development

The project is split in two parts: # Part 1 : Simulation Exercise to explore inference # Part 2 : Basic inferential analysis using the ToothGrowth data in the R datasets package

Useful Formulas and Calculations examples

Examples of t confidence intervals

Most Harmful events to Health and Economy

PA1_template.md Assignment 1

Testing the R-markdown process flow