Barebones introduction to statistical data analysis techniques, aimed at undergraduates doing research for the first time. This material in no way substitutes for a proper course, but hopefully provides enough to get started.
- Basic model fitting: just enough to get started with maximum likelihood methods for fitting model parameters, finding confidence intervals, evaluating goodness of fit, and comparing competing models.
Before running git pull
to update anything:
- Run
git status
to list any locally modified files. - For each modified file,
- if you want to keep your local changes,
- make a copy, e.g.
cp thisFile.ipynb thisFile_mine.ipynb
;
- make a copy, e.g.
- run
git checkout -- thisFile.ipynb
.
- if you want to keep your local changes,
Now it should be safe to git pull
.
- Physics 366: graduate/advanced undergraduate course in statistical methods in astrophysics, mostly Bayesian analysis
- LSSTC Data Science Fellowship Program, especially sessions 4 and 10
Adam Mantz. Any errors or unnecessary snarkiness is his fault.
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