The goal of this project is just to display that you've gotten used to working with the data and that you are on track to create your prediction algorithm. Please submit a report on R Pubs (http://rpubs.com/) that explains your exploratory analysis and your goals for the eventual app and algorithm. This document should be concise and explain only the major features of the data you have identified and briefly summarize your plans for creating the prediction algorithm and Shiny app in a way that would be understandable to a non-data scientist manager. You should make use of tables and plots to illustrate important summaries of the data set. The motivation for this project is to: 1. Demonstrate that you've downloaded the data and have successfully loaded it in. 2. Create a basic report of summary statistics about the data sets. 3. Report any interesting findings that you amassed so far. 4. Get feedback on your plans for creating a prediction algorithm and Shiny app.

Context You work for Motor Trend, a magazine about the automobile industry. Looking at a data set of a collection of cars, they are interested in exploring the relationship between a set of variables and miles per gallon (MPG) (outcome). They are particularly interested in the following two questions: “Is an automatic or manual transmission better for MPG” "Quantify the MPG difference between automatic and manual transmissions" Question Take the mtcars data set and write up an analysis to answer their question using regression models and exploratory data analyses. Your report must be: Written as a PDF printout of a compiled (using knitr) R markdown document. Brief. Roughly the equivalent of 2 pages or less for the main text. Supporting figures in an appendix can be included up to 5 total pages including the 2 for the main report. The appendix can only include figures. Include a first paragraph executive summary. Upload your PDF by clicking the Upload button below the text box. Peer Grading The criteria that your classmates will use to evaluate and grade your work are shown below. Each criteria is binary: (1 point = criteria met acceptably; 0 points = criteria not met acceptably) Your Course Project score will be the sum of the points and will count as 40% of your final grade in the course.

Storms and other severe weather events can cause both public health and economic problems for communities and municipalities. Many severe events can result in fatalities, injuries, and property damage, and preventing such outcomes to the extent possible is a key concern. This project involves exploring 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.

Assignment 2