The file describes how the script file "run_analysis.R" works

• Clean the working space in R. Set the working directory to where the UCI HAR Dataset is

• Read the training data. *Set the working directory to where the training data is stored. Read the data into R. Training data are store in 3 separate .txt files. One stores the features variables, one stores the y variable/the label, one stores the subject number.

• Read the test data. *Set the working directory to where the test data is stored. Read the data into R. Test data are store in 3 separate .txt files. One stores the features variables, one stores the y variable/the label, one stores the subject number.

• Extract only the mean() and std() features.

  • Activity names is stored in activity_labels.txt. Feature names is store in features.txt. Read these two files into R.
  • Extract features whose names has either mean() or std() in it. Names the features, and label the y variables using activity names.

• Merge data into one big dataset *Form the training dataset including features, labels and subjects *Form the testing dataset including features, labels and subjects *Append testing dataset to training dataset to form a big dataset.

• Form a tidy dataset