NutriNews Issue 7 2017 - Page 30

> L ike all scientific research, the foundation of nutritional sciences is the use of statistics to determine if a scientific finding is likely due to chance. In the past, studies were simpler, software was rudimentary or non- existent, and statistics was generally done by hand. > Now, a single study can generate massive amounts of data and rapid technological advancement has created powerful software and hardware. > Not long ago, it was mainly private corporations who created and distributed proprietary, or closed, statistical software i.e. SAS and IBM SPSS, which are companies as well as the software they sell. > Scientists relied on these companies to ensure that the statistics they ran were accurate and reliable, but at the cost of a hefty price tag and restrictive licensing to use the software. > However, over the last decade and a half, open source software has exponentially risen in popularity and use. > Open source means any software where the code for the software is publicly available to look at and improve, and is usually free to use. > Our economy, the web, and almost all electronic gadgets and devices you use in your everyday life run on open source software. > There are few open source statistical software, one being R. > It has rapidly gained massive traction within the scientific community because of its powerful statistical capabilities and programming features. > To keep things short, I'll only list three key reasons. > The first is that anyone is free to look over the code and verify that the results are accurate. there is no way to verify the code is correct. Instead, you have to trust the corporations when they say it works. > With proprietary software, > This goes against the scientific principles of reproducibility and replication. > Second, anyone can contribute to or develop extensions for R. > Unlike proprietary software that is bound by corporate bureaucracy and policies, cutting edge techniques can be distributed much sooner with open source software, which may or may not ever be developed in proprietary software. > Since the vast majority of statisticians globally use and contribute to R, advanced statistical techniques are available in R long before companies can incorporate them into their product. > Science is about using the latest tools to understand and analyze research results, which is a major advantage to using R over other software. Issue 3 | Nutrition of Everything | 24