SwiftKey Predictor Using Back-Off Good-Turing

In this report we look at three corpora of US English text, a set of internet blogs posts, a set of internet news articles, and a set of twitter messages.

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, or because they are tech geeks. One thing that people regularly do is quantify how much of a particular activity they do, but they rarely quantify how well they do it. In this project, your goal will be to use data from accelerometers on the belt, forearm, arm, and dumbell of 6 participants. They were asked to perform barbell lifts correctly and incorrectly in 5 different ways. More information is available from the website here: http://groupware.les.inf.puc-rio.br/har (see the section on the Weight Lifting Exercise Dataset).

The Effect of automatic or manual transmission on miles per gallon of cars

The response is the length of odontoblasts (teeth) in each of 10 guinea pigs at each of three dose levels of Vitamin C (0.5, 1, and 2 mg) with each of two delivery methods (orange juice or ascorbic acid)

In this project you will investigate the exponential distribution in R and compare it with the Central Limit Theorem.

The basic goal of this analysis is to explore the U.S. National Oceanic and Atmospheric Administration's (NOAA) Storm Database and answer some basic questions about severe weather events. This analysis answers the two questions: 1. Across the United States, which types of events (as indicated in the EVTYPE variable) are most harmful with respect to population health? 2. Across the United States, which types of events have the greatest economic consequences?