This is a set of tutorials for the CMS Data Analysis School (DAS) Statistics Short Exercise.
setup-libraries.ipynb
: setting up libraries usingCMSSW
0/exercise_0.ipynb
: a very shortPyROOT
/RooFit
tutorial1/exercise_1.ipynb
: analyzing a single count usingRooFit
/RooStats
2/exercise_2.ipynb
: analyzing three counts usingRooFit
/RooStats
3/exercise_3a.ipynb
: analyzing three counts usingcombine
3/exercise_3b.ipynb
: a realistic counting experiment usingcombine
3/exercise_3c.ipynb
: systematic uncertainties for data-driven background estimates usingcombine
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 usingcombine
(optional)
We will be using the Vanderbilt JupyterHub.
Hint! You may want to open this link in a new tab so that you can refer to these instructions for the next steps.
Point your browser to:
https://jupyter.accre.vanderbilt.edu/
If this is the first time using this JupyterHub, you should see:
Click the "Sign in with Jupyter ACCRE" button. On the following page, select CERN as your identity provider and click the "Log On" button. Then, enter your CERN credentials or use your CERN grid certificate to autheticate.
To start a new session, make sure the following drop-down options are selected:
- Select a Docker image: Default ACCRE Image v5
- Select a container size: 1 Core, 2GB RAM, 4 day timeout
Then click the orange Spawn button.
Now you should see the JupyterHub home directory. Click on "New" then "Terminal" in the top right to launch a new terminal.
In the terminal window, download the tutorials by typing:
git clone https://github.com/CERN-CMS-DAS-2023/statistics-das
Hint! If you want to cut-and-paste this command in the terminal, highlight the link and copy it as you usually would (Ctrl+c). To paste it, use Shift+Ctrl+v
Now go back to the Jupyter directory tab. There should be a new directory called statistics-das
. All of the tutorials and exercises are in there. Start by clicking on setup-libraries.ipynb
, changing the kernel to python 2 (tab at the top, Kernel -> Change kernel -> Python 2), and running it.
The indico page is: https://indico.cern.ch/event/1257234/
The twiki is: https://twiki.cern.ch/twiki/bin/edit/CMS/SWGuideCMSDataAnalysisSchoolCERN2023StatisticsExercise?t=1684950666;nowysiwyg=0