about the article ‘Common misconception about data analysis and statistics by Harvey J. Motulsky’

 The writer Harvey using concise and clear vocabulary, with easy-to-read pictures, and a wealth of literature. Provide readers with a clear subject for thinking on the common bias in statistics. The whole article states 5 points, analyze this matter from different situations. On this basis, we learned from the article is that some of the knowledge points we learned in class do not represent all situations. On the contrary, we must think about some special situations, combine with the common sense and not jump to conclusions. Such as the determination of p-value and mean quantifies variability, and do not explain too much on unimportant points that waste space. This reminds me of the time when I just started doing my statistics reports in my previous class. I was doing a data analysis for a couple of samples, I did not make enough large sample size, I calculated the wrong p-value which made me misunderstand when estimating the answer. As said in the article, the sample size will affect the result. After reading this article, it reminds me a lot that when I am working on the statistics assignment, I will make more attention on these common misconception. 

Reference: Motulsky, H. J. (2014). Common misconceptions about data analysis and statistics. Naunyn-Schmiedeberg’s Archives of Pharmacology, 387(11), 1017–1023. https://doi.org/10.1007/s00210-014-1037-6

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