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moocrr-reproducibility-study
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In this project, we gather reproduction attempts from the Challenger In this project, we gather reproduction attempts from the Challenger
study. In particular, we try to reperform some of the analysis study. In particular, we try to reperform some of the analysis
provided in *Risk Analysis of the Space Shuttle: Pre-Challenger provided in *Risk Analysis of the Space Shuttle: Pre-Challenger
Prediction of Failure* by *Siddhartha R. Dalal, Edward B. Fowlkes, Prediction of Failure* by *Siddhartha R. Dalal, Edward B. Fowlkes, Bruce
Bruce Hoadley* published in *Journal of the American Statistical Hoadley* published in *Journal of the American Statistical Association*,
Association*, Vol. 84, No. 408 (Dec., 1989), pp. 945-957 and available 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
at is [[http://www.jstor.org/stable/2290069][the official JASA webpage]])
[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 On the fourth page of this article, they indicate that the maximum
likelihood estimates of the logistic regression using only temperature likelihood estimates of the logistic regression using only temperature
are: $\hat{\alpha}=5.085$ and $\hat{\beta}=-0.1156$ and their are: $\hat{\alpha}=5.085$ and $\hat{\beta}=-0.1156$ and their
asymptotic standard errors are $s_{\hat{\alpha}}=3.052$ and asymptotic standard errors are $s_{\hat{\alpha}}=3.052$ and
$s_{\hat{\beta}}=0.047$. The Goodness of fit indicated for this model $s_{\hat{\beta}}=0.047$. The Goodness of fit indicated for this model
was $G^2=18.086$ with 21 degrees of freedom. Our goal is to reproduce 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, the computation behind these values and the Figure 4 of this article,
possibly in a nicer looking way. possibly in a nicer looking way.
[**Here is our successful replication of Dalal et al. results using *[[file:challenger.pdf][Here is our successful replication of Dalal et al. results using R]]*.
R**](file:challenger.pdf).
In case it helps, we provide you with two implementations of this case 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 study but we encourage you to *reimplement them by yourself* using both
your favourite language and an other language you do not know yet. your favourite language and an other language you do not know yet.
- A [Jupyter Python3 notebook](file:src/Python3/challenger.ipynb) - A [[file:src/Python3/challenger.ipynb][Jupyter Python3 notebook]]
- An [Rmarkdown document](file:src/R/challenger.Rmd) - An [[file:src/R/challenger.Rmd][Rmarkdown document]]
Then **update the [meta-study result table available Then *update the [[file:results.org][meta-study result table available here]] with your own
here](file:results.org) with your own results**. results*.
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