This study was commissioned to predict how a subject performed an exercise. The data used for this project was collected from a range of wireless activity wristbands. The wristbands were worn by the subjects as they performed excercies in 5 different ways. To study the data I broke the source data into a training and testing set. I experimented with 2 training models; Decision Tree and Random Forest. The decision tree performed very poorly which is likely to be caused by a lack of homogeneity in the data. We know that random forest is one of the most accurate models and it proved itself here with this data.

This App was created for the Data Science Capstone Project. The skills used in this project were learnt from the 9 preceeding courses of this specialization. The aim of this app is to predict the next word that the user will type. This type of application could benefits the billions of mobile phone users around the world as they use their devices to for social networking, banking, etc.

This report is a brief introduction into the shiny text predictor.

This presentation is being used used as a part of my analysis of World Bank's Climate Change Data. The analysis is a rather simple one. It allows the user to use sliders to filter the data. The app can be found here: https://ricej2.shinyapps.io/UrbanGrowth/

This study was commissioned to examine the relationship between a set of variables the resulting miles per gallon (MPG). A key consideration of this study is the transmission type (Manual vs Automatic). The results will be provided to Motor Trend. Regression model techniques are used to draw conclusions which would be provided to Motor Trend for their decision making. The study has shown that manual would better for MPG and there is quite a significant difference between the transmission types. If using a regression model, weight is the best indicator.

The purpose of this analysis is illustrate the validity of the Central Limit Theorem(CLT). In order to do this, a random sample with be taken and its statistical qualities are compared to the CLT.

The purpose of this analysis is to analyse tooth growth by supp and dose. First we will take a brief look at the data, perform a couple tests and finally offer conclusions.

This is an analysis of sample data from the U.S. National Oceanic and Atmospheric Administration's (NOAA) storm database. This database tracks characteristics of major storms and weather events in the United States, including when and where they occur, as well as estimates of any fatalities, injuries, and property damage. In this brief analysis I will seek to present the greatest impacts of these weather events from a health and economical perspective. Two dichotomous plots are used for the aforementioned perspective. Both the source code and results are shown in this document.