Merge pull request #29 from AFJohan92/gh-pages

Adding links to Zoom recordings

_episodes/07-preselection.md

@@ -16,6 +16,8 @@ keypoints:
 - "Preselected events should be in good regions of the detector with appropriate filters"
 - "Stacked histograms are an important tool for creating cuts"
 ---
+Recording files of this session are in [cernbox](https://cernbox.cern.ch/index.php/s/uibnZgUrfC0HAqn)
+
 # Introduction
 
 A preselection serves two purposes, first to ensure that passing events only utilize a "good" region of the detector with

_episodes/09-optimisation.md

@@ -17,6 +17,7 @@ keypoints:
 - "The traditional way of optimizing selections is to apply N-1 (all-but one) cuts and findng peak of significance curve in removed cut."
 - "Boosted Decision Trees and other multivariate optimization techniques are also widely used."
 ---
+Recording files of this session are in [cernbox](https://cernbox.cern.ch/index.php/s/uibnZgUrfC0HAqn)
 
 ## Setup Ahead of Session
 To more efficiently help with debugging, we are going to use remote access of your terminal through [tmate](https://tmate.io/). The way this application works is that you can initialize it (by calling 'tmate') and it'll start a session of your terminal that is viewable and editable online. In the website linked it shows how that looks like. If you feel comfortable letting the facilitators use this with you, follow the steps below to install tmate. 

_episodes/11-background_control_regions.md

@@ -23,6 +23,7 @@ keypoints:
 - "Validation regions are designed to lie orthgonal but between CRs and SRs, perhaps with lower target BG purity, to test the corrections extracted from the CR that will be applied to SRs."
 - "Blinding is the convention of not looking at data in the SR (or any signal-enriched selection)."
 ---
+Recording files of this session are in [cernbox](https://cernbox.cern.ch/index.php/s/uibnZgUrfC0HAqn)
 
 ## Backgrounds to the Analysis
 

_episodes/12-background_estimation.md

@@ -11,6 +11,7 @@ keypoints:
 - "We can simultaneously fit several backgrounds by defining the appropriate observables/axes, i.e. m<sub>t</sub> vs m<sub>tW</sub>."
 - "2D Alphabet is a method of fitting a polynomial function to a space (except the SR), to model the multi-jet background, and also serves as an interfae to other tools." 
 ---
+Recording files of this session are in [cernbox](https://cernbox.cern.ch/index.php/s/uibnZgUrfC0HAqn)
 
 ## Idea of 2D Alphabet
 Normally, we do a shape hunt along some observable and measure our background is near-by kintemtic regions to estimate its expected yield in the signal region. For our case, there is a clever way to do all these tasks simultaneously. Since we are scanning across m<sub>tW</sub>, with a window designated as a Signal Region, we can use all the non-window space to fit a smooth function that extrapolates over the SR window.