This file gives a description of what the purpose of the project is, what files are included in the project and the instructions to produce the results.
- Download the files containing data collected from accelerometers in a particular experiment. Details of this experiment can be found at http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones.
- Extract the files.
- Merge the training and the test sets to create one data set.
- Extract the measurements on the mean and standard deviation for each measurement.
- Use descriptive activity names to name the activities in the data set.
- Appropriately label the data set with descriptive variable names.
- From the data set in step 6, create a second, independent tidy data set with the average of each variable for each activity and each subject.
- Save the tidy data set.
- 'README.md': this file.
- 'CodeBook.md': describes the tidy data set created and saved as per steps 7 and 8 above.
- 'download_data.R': R script described below.
- 'run_analysis.R': R script described below.
The project work is divided into two scripts, download_data.R and run_analysis.R. These are to be run one after the other in this order, from the same working directory, using the following commands.
source("download_data.R")
source("run_analysis.R")
This script downloads the required data set and extracts the contents in the current working directory.
This script assumes that the first script, download_data.R, was run, or that the UCI HAR Dataset folder is in the current working directory. It then goes on to perform steps 3 to 8 described above.