Describes a Shiny web app that implements an n-gram word prediction model.

Describes design of a predictive text model using n-grams.

Created with r-leaflet and RStudio.

This Shiny app draws three different types of univariate graphs (histogram, box plot, scatter plot) using R’s Iris dataset.

Richard A. Lent

This machine learning project used data from accelerometer devices worn on the belt, forearm, arm, and barbell of six participants, who were asked to perform barbell lifts correctly and incorrectly in five different ways. The goal was to predict the manner in which participants did the exercise. The dependent variable in a k-Nearest Neighbor classification had five classes: A, exercise performed exactly according to the specification; B, throwing the elbows to the front; C, lifting the dumbbell only halfway; D, lowering the dumbbell only halfway; and E, throwing the hips to the front. Class A corresponds to the correct execution of the exercise, while the other four classes correspond to common mistakes.

We examined the effect of transmission type on vehicle mileage, using R’s mtcars dataset. The data consist of variables on fuel consumption and 10 aspects of automobile design and performance for 32 cars from 1973 and 1974. Analysis of several multiple regression models revealed that having a manual transmission can increase vehicle mileage up to 7.2 miles per gallon, on average, compared to having an automatic transmission. However, the effect of transmission type was only statistically significant when transmission type was the sole predictor of mileage; significance of transmission type disappeared when other variables were added to the models. In general, transmission type does affect vehicle mileage but the magnitude of the effect varies according to the presence of numerous other covariates, each of which contributes a small, but cumulatively significant, influence on mileage.

Using R’s ToothGrowth dataset (goo.gl/x56NyM), we examine tooth growth in Guinea pigs in relation to vitamin C dose level and method of delivery.

This project investigates the exponential distribution in R in relation to the Central Limit Theorem. Using 1000 simulations, we investigate the properties of the distribution of the mean of 40 exponentials.

We used the U.S. National Oceanic and Atmospheric Administration’s (NOAA) storm database to examine some of the health and economic consequences of severe weather events over the period from 1950 to 2011. Weather events from the NOAA database were reclassified into 13 categories for analysis. Hurricanes and extreme heat events had the greatest health consequences in terms of number of fatalities and number of injuries caused. Hurricanes by far had the greatest economic impact in terms of property damage, whereas ice-related events caused the greatest amount of crop damage.