##Goal The purpose of this project is to demonstrate my ability to collect, work with, and clean a data set.

The goal is to prepare tidy data that can be used for later analysis.

I am submitting:

1. a tidy data set as described below,

2. a link to a Github repository with my script for performing the analysis, and

3. a code book that describes the variables, the data, and any transformations or work that I performed to clean up the data called codebook3.md.

####This repo explains how all of the scripts work and how they are connected.

One of the most exciting areas in all of data science right now is wearable computing - see for example

http://www.insideactivitytracking.com/data-science-activity-tracking-and-the-battle-for-the-worlds-top-sports-brand

Companies like Fitbit, Nike, and Jawbone Up are racing to develop the most advanced algorithms to attract new users. The data linked to from the course website represent data collected from the accelerometers from the Samsung Galaxy S smartphone.

A full description is available at the site where the data was obtained:

http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones

http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones

Here are the data for the project:

https://d396qusza40orc.cloudfront.net/getdata/projectfiles/UCI%20HAR%20Dataset.zip https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip

##This repo contains:

###One R script called run_analysis.R that does the following:

###The final dataset called tidydata.txt, in csv format

##Steps of the cleaning process