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Like everything in life, open access has its good and bad sides. As part of open access week, we’ll give a brief rundown of some of the positive and negative aspects of publishing open access.


Advantage 1: Free for all


In our previous post, we talked about the importance of avoiding verbiage and using overly long words for their own sake, to keep the expression in your paper clear, simple, and readable. While simple, concise expression is key to communicating your research clearly, it’s also important to use language that maintains the right tone for a scientific publication that will be read by a highly accomplished audience of researchers.


Shakespeare wrote that brevity is the soul of wit. When writing a manuscript, the complexity of your research may not always make it easy to keep your text brief, but it is still important to express ideas clearly and succinctly, with a minimum of unnecessary words.



There are a lot of journals out there to choose from and, unfortunately, not all of them are reputable. So how do you know which journals are good to submit to or have sent you a legitimate request for peer review? We’ve provided here a short guide to help you distinguish reputable journals from non-reputable journals. These items are some of the important factors to look for that can help you identify whether a journal’s practices are likely to be trustworthy.


Signs of a non-reputable or predatory publisher:


As is so often the case, the things we may have learned as “rules” for starting a sentence are not always universal. We may have been taught that a sentence should never start with a conjunction, or an acronym, or an Arabic numeral, but is that always the case?


Why do we use analysis of variance (ANOVA) when we are interested in the differences among means?

ANOVA is used to compare differences of means among more than 2 groups. It does this by looking at variation in the data and where that variation is found (hence its name). Specifically, ANOVA compares the amount of variation between groups with the amount of variation within groups. It can be used for both observational and experimental studies.

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