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
[here](https://studies2.hec.fr/jahia/webdav/site/hec/shared/sites/czellarv/acces_anonyme/OringJASA_1989.pdf)
(here is [the official JASA
webpage](http://www.jstor.org/stable/2290069)).

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.


[*Here is our successful replication of Dalal et al. results using
R*](challenger.pdf).

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 [Jupyter Python3 notebook](src/Python3/challenger.ipynb)
    -   An [Rmarkdown document](src/R/challenger.Rmd)
2.  Then **update the [meta-study result table available
    here](results.md) with your own results**.

