CMS Data Analysis School (CMSDAS): Statistics Short Exercise

Introduction

This is a set of tutorials for the CMS Data Analysis School (CMSDAS) Statistics Short Exercise that are implemented in Jupyter notebooks. The tutorials provide a concise introduction to key ideas in statistics and a few of the statistical analysis tools commonly used in high-energy physics.

Notebooks

notebooks	description
0/exercise_0.ipynb	a very short PyROOT/RooFit tutorial
1/exercise_1a.ipynb	analyzing a single count using RooFit/RooStats
1/exercise_1b.ipynb	analyzing a single count using RooFit/RooStats
2/exercise_2.ipynb	analyzing three counts using RooFit/RooStats
3/exercise_3a.ipynb	analyzing three counts using combine
3/exercise_3b.ipynb	a realistic counting experiment using combine
3/exercise_3c.ipynb	systematic uncertainties for data-driven background estimates using combine
4/exercise_4.ipynb	binned fit to Run I H->gg data (optional)
5/exercise_5.ipynb	unbinned fit to Type Ia supernovae distance modulus/red shift data (optional)
6/exercise_6.ipynb	histogram template analysis using combine (optional)

Getting Started on Swan

1. Go to http://swan.web.cern.ch/ with your browser.

2. Sign on to your CERN account username and password using Single Sign On (SSO).

3. Under Configure Environment, click the Start my Session button.

you can use the default parameters: Software Stack: 104a, Platform: CentOS 7 (gcc 11), Number of cores: 4, Memory: 8 GB, Spark cluster: None

4. In the upper right corner, click on the New Terminal button >_ to open a terminal window in a new tab in your browser. Go to the new tab and type ls, then return (or enter) in the terminal window. You will see a list of the files in your CERNBox home directory. You may also see a directory (i.e., folder) called SWAN_projects. If one does not exist, create one using:

mkdir SWAN_projects

5. In the terminal window, navigate to SWAN_projects and download the tutorials by typing:

cd
cd SWAN_projects
git clone https://github.com/FNALLPC/statistics-das.git

6. In the original tab, click on the CERNBox button at the top of the page and click on the folder SWAN_projects. There should be a new directory called statistics-das. All of the tutorials and exercises are in there.
7. Open and execute the contents of setup-libraries.ipynb
8. To open a notebook, e.g. statistics-das/0/exercise_0.ipynb, simply click on the file.

If you face compilation or jupyter kernel errors when running combine from the jupyter notebook in exercise 3, you can compile the combine tool in the Swan terminal by doing source build-combine-standalone.sh.

Notebook Tips

Jupyter notebooks are structured into cells. It is recommended that you execute the notebooks one cell at a time to ensure that each cell works as expected. And, yes, cells should be executed sequentially! Of course, if you're careful, you can go back and re-execute cells. But remember jupyter notebooks are ``sticky'' in that the notebook pays attention to the order in which cells have been executed. This can lead to confusion. If things get really messed up, it's usually better to re-launch the jupyter kernel and start again from scratch.

Some useful shortcuts

• Use esc r to disable a cell
• Use esc y to reactivate it
• Use esc m to go to markdown mode. Markdown is the typesetting language used in jupyter notebooks. In a markdown cell, double tap the mouse or glide pad (on your laptop) to go to edit mode.
• Shift + return to execute a cell (including markdown cells).
• If the equations don't typeset, try double tapping the cell again, and re-execute it.

Links

• FNAL github site: https://fnallpc.github.io/statistics-das/

• The Mattermost for live support is: https://mattermost.web.cern.ch/cmsdaslpc2024/channels/shortex-statistics. (If you don't have access, see the general CMSDAS instructions for the Mattermost signup link.)

• The twiki is: https://twiki.cern.ch/twiki/bin/view/CMS/SWGuideCMSDataAnalysisSchoolLPC2024StatisticsExercise