Introduction

Overview

Teaching: 5 min
Exercises: 0 min

Questions

• What is ROOT?

• What can I learn here?

Objectives

• Understand what you can learn in this lesson!

Hi there, a warm welcome to the lesson about efficient analysis with ROOT!

What is ROOT?

In short, it’s an open-source data analysis framework used by high energy physics and others, which lets you save and access your experiment’s data, allows you to process the data in a computationally efficient and statistically sound way and gives you access to all tools to produce publication-quality results.

What can I learn here?

We would like to show you how you can perform efficient data analysis with ROOT! Starting with getting access to ROOT, you will learn the advantages of ROOT in C++ and Python. Next, we want to introduce you to a selection of features, which we see commonly used in a typical analysis. Another ingredient for efficient analysis is a simple way to get help quickly and therefore you will learn where you can find support. The last sections introduce you to the modern way to process data with ROOT and walks you through a full analysis based on CMS NanoAOD files. You can learn how to go efficiently from the initial datasets to the result plots, all powered by ROOT!

Key Points

• You’ll learn how to install ROOT on your system or get access to systems with ROOT pre-installed!

• You’ll learn how to use ROOT in C++ and Python!

• You’ll learn about commonly used features in ROOT!

• You’ll learn how to get help with ROOT!

• You’ll learn to do efficient data analysis with an example based on NanoAOD files!