It is now possible to collect a large amount of data about personal movement using activity monitoring devices such as a Fitbit, Nike Fuelband, or Jawbone Up. These type of devices are part of the “quantified self” movement – a group of enthusiasts who take measurements about themselves regularly to improve their health, to find patterns in their behavior, or because they are tech geeks. But these data remain under-utilized both because the raw data are hard to obtain and there is a lack of statistical methods and software for processing and interpreting the data.
We make use of data from a personal activity monitoring device. This device collects data at 5 minute intervals through out the day. The data consists of two months of data from an anonymous individual collected during the months of October and November, 2012 and include the number of steps taken in 5 minute intervals each day.
This repo constins the follwing files.
- data.csv : the file with the raw data;
- activityMonitoringAnalysis.Rmd : the Rmd file containing the analysis;
- activityMonitoringAnalysis.html : the resulting .html file
The code for the analysis is displayed in the .rmd file. The results can be viewed in the .html file.
We are able to effectively describe the dailiy activity pattern given by the activity monitoring devices considered.