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Submission for the final project for the Getting and Cleaning Data class offered through Coursera.

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Getting and Cleaning Data Course Project

Peter J. Ireland

Submission for the final project for the Getting and Cleaning Data class offered through Coursera.

The script run_analysis.R is used for the analysis. It performs the following steps:

  1. Downloads and unzips the files.
  2. Merges the training and the test sets to create one data set.
  3. Extracts only the measurements on the mean and standard deviation for each measurement.
  4. Uses descriptive activity names to name the activities in the data set.
  5. Appropriately labels the data set with descriptive variable names.
  6. From the data set in step 4, creates a second, independent tidy data set with the average of each variable for each activity and each subject.

The tidy data set generated in Step 5 above is included in this repository as human_activity_recognition.txt. The codebook is provided as codebook.pdf.

The script was run using
R version 3.2.3 Patched (2015-12-17 r69782)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
Running under: OS X 10.10.5 (Yosemite).
It uses two libraries: dplyr_0.4.3 and magrittr_1.5.

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Submission for the final project for the Getting and Cleaning Data class offered through Coursera.

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