Evaluation of General Sources

      The controversy I've decided to perform a postmortem on within my field is that there is power failure within the field of neuroscience; meaning that the sample sizes for studies partaken in the field are too small to be of statistical importance or to give truthful analysis of a subject. The controversy mostly surrounds one specific work, called " Power Failure: Why Small Sample Size Undermines the Reliability of Neuroscience" by a collaboration of authors, which has sprouted countless analysis and responses. I will evaluate that source as well as a response to it called "Is Neuroscience Really Too Small?" 


Power Failure
    The URL for this main source is http://www.nature.com/nrn/journal/v14/n5/full/nrn3475.html#B1; having a source end with .com implies that the source is from a commercial entity and that any entity is allowed to register to use it; it has become the main domain. While this could perfectly well be a credible source, the .com does not instill the largest amount of confidence. Depending on what information one is looking for a more specific sort of domain like .edu, for educational organizations only, or .gov, which is limited to use by the government.
     The authors for this source number seven. Katherine S. Button, John P. A. Ioannidis, Claire Mokrysz, Brian A. Nosek, Jonathan Flint, Emma S. J. Robinson, and Marcus R. Munafòl. All of the authors of this source are either Doctors of Philosophy (PhDs), Doctor of Medicine (MD), Doctor of Science (D.Sc.), or Masters in Science (M.Sc.) and PhD students at universities. SO pertaining to the subject they are very qualified to speak on scientific studies.
     The last update of the article may have been in April 2013 when it says the article was "corrected".
     The purpose of this text is to educate the audience about the potential of small sample sizes affecting the reliability of studies within neuroscience. The source is promoting the idea that for neuroscience studies to be more reliable they need larger sample pools from which to test.
      The graphics within this work are primarily graphs and charts showing how different levels of statistical power effect the look of results.
      The position of the paper I would not say is one-sided, however it is taking a side. It has more than a hundred references to prove its credibility and other sources around the web that have responded to the paper have agreed with it's point as well. If the viewers of the website believe the author I would not say anyone directly profits but there can be examples of those that it would be unprofitable for if viewers read and believed it. If a reader agrees with the authors' views then they may go out into the world and believe that any neuroscience study is incorrect or has too small of a sample to make a definitive claim.
      Throughout the text the authors provide multiple links so that the readers may research or look to understand deeper certain concepts. All of the references are linked articles or books with reputable authors.
   

Thomas Fisher Rare Book Library, UofT. "Dissection of the brain"
02/03/2014 via Flickr. Attribution 2.0 Generic 

Really Too Small
     The URL for this source is http://blogs.discovermagazine.com/neuroskeptic/2013/08/10/is-neuroscience-too-small/#.VrFedPlViko. It is like the other source that is is a .com domain and of suspicious credibility.
     The author for this source, which is a blog connected to a magazine, only seems to go by the name "Neuroskeptic". So there is not really much of a way to check how credible the author is, however, a short bio about the person states that they are a British neuroscientist, although there is no proof that I can find, like a name or something of that sort. But from the thousands of discussions on neuroscience subjects within this blog that the author must have some sort of credibility.
      There is no shown update on the post, it was posted after the first article it discusses in August of 2013.
      The purpose of this text is to discuss the first text discussed. It is a sort of response to the article on why neuroscience is messed up by the prominent amount of too small sample sizes. This article specifically educates the readers a little about the subject but mostly it is, as the author proclaims themselves a skeptic, trying to ensure that the source is truly correctly done, which they seem skeptical about.
      The couple of graphics within this blog post are graphs trying to show some mathematical function from the statistics of the first article that this author thinks may have been done incorrectly.
      The position of this paper is that primarily the original article is correct in its statements that there is a power failure and too small sample sizes throughout neuroscience, except that the graphical calculations for the samples may have been done incorrectly. If readers believe what this author says then he profits in getting more credibility while the authors of the other source get discredited and the research does not seem as irrefutable.
      The links in this blog post are primarily to definitions of words that the readers may not understand just off the top of their heads and all the main link of this blog post is the link to the article it is responding to or about.