Elite BGS Science Hypotheses, Test Data, and thus proven theories that means all your base belong to us.
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Please send any errors or corrections to the SINC team at SINC Discord
This is a repo containing a list of basic research into Elite Dangerous: Odyssey to validate assumptions on the background simulation, questions, hypotheses, predictions, variables, controlled variables, risk assessment, materials (if any), method and design, results with test data. This repo is a way to document experiments and their results that validate or disprove the data we see.
Sadly, FDev don’t often document what are the limits or assumptions of BGS, so it’s up to us to work out what’s helpful, and when does it become more useful to spread effort over alts. We really want to make BGS less a second job and more of a passion by giving Cmdrs the knowledge to best use their time.
We will use the standard scientific method, using sequential analysis to optimize results. What this means is that we will try a few things until it is clear that we have either concluded that it has no real effect, but also to explore what are the likely variables for a particular question. This may require some level of probability or other maths capability to ensure that our biases are not the biases of the data, or allow the replication of results using our methodology.
We will go into each experiment with zero assumptions. The best science are results that surprise the researchers.
The papers in this repo are built using markdown-paper. Install:
sudo apt-get install pandoc pandoc-citeproc texlive ghostscript texlive-bibtex-extra texlive-science fonts-lato texlive-fonts-extra texlive-publishers
pip install pandoc-fignos
sudo dnf install pandoc texlive-scheme-medium ghostscript texlive-collection-bibtexextra texlive-collection-mathscience lato-fonts texlive-lato texlive-latex-fonts texlive-collection-fontsrecommended texlive-collection-latexrecommended texlive-collection-fontsextra texlive-collection-publishers ghc-citeproc
pip install pandoc-fignos pandoc-citeproc
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The following guides are annotated, but otherwise have the original text as found on the Internet:
Some ideas on optimizing the analysis of results are here https://www.britannica.com/science/statistics/Residual-analysis