You should create one R script called run_analysis.R that does the following.

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

1. Download the data source and extract it on your local drive. Note that a folder UCI HAR Dataset will be created.
2. The script run_analysis.R should be placed in the parent folder of UCI HAR Dataset
3. Set the parent folder of UCI HAR Dataset as your working directory using setwd() function.
4. Run source("run_analysis.R"), then it will generate a new file tiny_data.txt in your working directory.

data.table - powerful library for fast aggregation of large data. You can install the package by executing install.packages("data.table")