W.P Hangage addresses five important questions that he urges readers to keep in mind when viewing scientific literature. These questions are to help audience members identify when authors of a certain paper may be exaggerating their findings to seem more important than they truly are (as we’ve seen throughout the term, not all peer reviewed papers are great papers.) One of the first questions he tells readers to keep in mind is “can experiments detect differences that matter?” The significance of this question applies when looking at scientific literature because oftentimes most readers are not too familiar with the methods being used for the study and just assume it is relevant based on what the authors had written. Most experiments with microbial communities work by categorizing which bacteria phyla are present but does that tell us that all bacteria under a certain phyla are bad, or do we have to keep investing further to see?The second question asked is “Does the study show causation or correlation?”. I think this question is very valuable, especially when looking at recent microbial studies. Many readers often confuse correlation and causation and I do think it is one of the most valuable questions to ask. I think this is the most valuable question to ask because as mentioned earlier, lots of experiments work by grouping the bacteria present into their corresponding phyla, but that does not necessarily tell us that bacteria from a specific phylum or even family is the cause for a disease as there is still a large amount of diversity present within a bacteria phylum. The Third question Hangage tells his readers to keep in mind is “What is the mechanism?” which ties in with the second question. After authors claim a relationship whether it is causation or correlation, readers should look in the article for one affects the other. Another question asked is “How much do these experiments reflect reality?” which is a valuable question when discussing microbial communities. Many experiments as Hangage mentions are performed on lab mice which can have very different gut compositions and reactions in comparison to humans, so it is important to keep in mind how applicable each experiment is. “Could anything else explain the results?” is the final question asked and is important because this is where readers should look for any possible design failures or results that perhaps did not fit the data to see if there is a reason they got the results they did.