What is repdata_peerassessment1?

This repository contains a student's coursework submission for a class on reproducible research. The assignment asks students to analyze real data from a fitness tracker and write up their findings in a way that other people can understand and verify. The core task is straightforward: you have two months of step-count data collected at 5-minute intervals from an anonymous person, and you need to answer specific questions about their activity patterns. For example, how many steps did they take on average each day? When during the day were they most active? Do they move more on weekends than weekdays? The key twist is that some of the data is missing, so you also have to figure out a reasonable way to fill in the gaps before drawing your conclusions. What makes this assignment "reproducible research" is the process. Instead of just showing the final answers, you write all your code alongside your explanation in a special document format called R markdown. This means anyone reading your work can see exactly what you did, run the same code themselves if they want, and verify that your conclusions actually follow from the data. The assignment requires you to submit not just your analysis but also the HTML report it generates, plus any charts you created, all committed to GitHub so instructors and peers can review everything. This is a genuine university assignment from a Johns Hopkins online course on reproducible data analysis. It's designed to teach students how to work with real data, clean it up, analyze it, and communicate their process transparently, skills that matter whether you're doing academic research, journalism, or data work in industry. The peer review component means other students will evaluate whether the code is clear and the logic is sound.