This lesson is being piloted (Beta version)

Simplified Run 2 Analysis


What is this lesson about?

Welcome. In this lesson you will:

  • Learn how to connect everything you have learned so far in order to exercise a full (or almost full) analysis example
  • Learn how to implement the most usual ingredients of an analysis and the construct an analysis chain
    • Select subsets of the data and Monte Carlo that are aimed at maximizing the significance of your signal
  • Be able to produce plots to show the results
  • Learn about estimating systematics and statistical aspects of the analysis
  • Use all of this to measure some physical quanity and estimate the uncertainties on your measurement


To follow this lesson you need to start the python tools Docker container from the pre-exercises:

If you have already successfully installed and run the Docker example with python tools, then you need only execute the following command.

docker start -i my_python  #give the name of your container

If this doesn’t work, return to the python tools Docker container lesson to work through how to start the container.


Setup Download files required for the lesson
00:00 1. Pre-lesson reading and computational setup What analysis will we be doing?
00:50 2. Introduction What analysis will we be doing?
What is columnar analysis?
Why do we use coffea?
What are coffea main components?
What are schemas?
01:30 3. Coffea Analysis What is the general plan for the analysis?
What are the selection requirements?
How do I implement additional selection requirements?
What are Coffea Processors?
How do I run an analysis with Coffea?
02:50 4. Break Should we get some coffea?
03:20 5. Systematics and Statistics How are systematic variations handled in Coffea?
How do we perform statistical inference?
What tools do we use?
How do we visualize and interpret our results?
04:50 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.