Monthly Archives: April 2016

Why showing raw data matters

Bar and line graphs with standard deviation (SD) or standard error (SE) error bars are often used to visually present continuous data from laboratory studies with small sample sizes. Last year the journal PloS Biology published a paper showing that presenting such data this way is problematic for the following reasons: bar and line graphs conceal how data are distributed

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R: Visualize and calculate a Pearson correlation

Scientists are often interested in understanding the relationship between two variables. One simple way to understand and quantify a relationship between two variables is correlation analysis. Assumptions. This post assumes you understand the theory behind correlation analysis and have a working knowledge of R; it focuses on how to run this type of analysis in R. The dataset: foot length

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