In this project, we gather reproduction attempts from the Challenger
study. In particular, we try to reperform some of the analysis
provided in /Risk Analysis of the Space Shuttle: Pre-Challenger
Prediction of Failure/ by /Siddhartha R. Dalal, Edward B. Fowlkes,
Bruce Hoadley/ published in /Journal of the American Statistical
Association/, Vol. 84, No. 408 (Dec., 1989), pp. 945-957 and available
at [[https://studies2.hec.fr/jahia/webdav/site/hec/shared/sites/czellarv/acces_anonyme/OringJASA_1989.pdf][here]] (here is [[http://www.jstor.org/stable/2290069][the official JASA webpage]]).

On the fourth page of this article, they indicate that the maximum
likelihood estimates of the logistic regression using only temperature
are: $\hat{\alpha}=5.085$ and $\hat{\beta}=-0.1156$ and their
asymptotic standard errors are $s_{\hat{\alpha}}=3.052$ and
$s_{\hat{\beta}}=0.047$. The Goodness of fit indicated for this model
was $G^{2}=18.086$ with 21 degrees of freedom. Our goal is to reproduce
the computation behind these values and the Figure 4 of this article,
possibly in a nicer looking way.

#+BEGIN_CENTER
*[[file:challenger.pdf][Here is our successful replication of Dalal et al. results using R]]*.
#+END_CENTER

1. Try to *replicate the computation* from Dalal et al. In case it
   helps, we provide you with two implementations of this case study
   but we encourage you to *reimplement them by yourself* using both
   your favourite language and an other language you do not know yet.
   - A [[file:src/Python3/challenger.ipynb][Jupyter Python3 notebook]]
   - An [[file:src/R/challenger.Rmd][Rmarkdown document]]
2. Then *update the [[file:results.org][meta-study result table available here]] with your
   own results*.