This directory/repository contains the run_analysis.R script to process and merge the UCI Human Activity Recognition (UCI HAR) dataset for the Getting and Cleaning Course Project.

1. README.MD # this file which describes the files in the repostiory

2. run_analysis.R # the R script which does the processing

3. CodeBook.md # the file that describes the variables in the tidy dataset

4. Recipe.md # the explicit instructions for producing the tidy dataset

Brad Banko, 11/23/2014 Getting and Cleaning Data Course Johns Hopkins School of Public Health

This is a Markdown file which allows for readable documentation that can also be formatted and cast in html directly. Here is a sample.

The four things I have:

• The raw data is the UCI feature activity testing and training datasets with activity labels and subject IDs:

  raw data

  • Unpack this data in the directory where the run_analysis.R script is.

• A tidy data set (tidyData.csv) is a summary of the raw dataset subsetting 86 of the 561-feature vector time and frequency domain variables which have either "mean" or "std" (for standard deviation) in their names. The mean values of the 86 feature variables over the subject ID and activity type labels have been used for the tidy data set.

• For the detailed description of the variables in the tidy data set are listed in the CodeBook.md.

• For an explicit and exact recipe for transforming the raw dataset into the tidy dataset, see Recipe.md