| Title |
Common misconceptions about data analysis and statistics
|
|---|---|
| Published in |
Naunyn-Schmiedeberg's Archives of Pharmacology, September 2014
|
| DOI | 10.1007/s00210-014-1037-6 |
| Pubmed ID | |
| Authors |
Harvey J. Motulsky |
| Abstract |
Ideally, any experienced investigator with the right tools should be able to reproduce a finding published in a peer-reviewed biomedical science journal. In fact, the reproducibility of a large percentage of published findings has been questioned. Undoubtedly, there are many reasons for this, but one reason maybe that investigators fool themselves due to a poor understanding of statistical concepts. In particular, investigators often make these mistakes: 1. P-Hacking. This is when you reanalyze a data set in many different ways, or perhaps reanalyze with additional replicates, until you get the result you want. 2. Overemphasis on P values rather than on the actual size of the observed effect. 3. Overuse of statistical hypothesis testing, and being seduced by the word "significant". 4. Overreliance on standard errors, which are often misunderstood. |
X Demographics
The data shown below were collected from the profiles of 49 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | 22% |
| United Kingdom | 9 | 18% |
| Australia | 2 | 4% |
| Portugal | 2 | 4% |
| France | 1 | 2% |
| Germany | 1 | 2% |
| Switzerland | 1 | 2% |
| Turkey | 1 | 2% |
| Canada | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 18 | 37% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 24 | 49% |
| Members of the public | 21 | 43% |
| Science communicators (journalists, bloggers, editors) | 3 | 6% |
| Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 2% |
| Sweden | 1 | <1% |
| Germany | 1 | <1% |
| Unknown | 118 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 33 | 27% |
| Researcher | 26 | 21% |
| Student > Master | 15 | 12% |
| Professor > Associate Professor | 8 | 7% |
| Other | 7 | 6% |
| Other | 21 | 17% |
| Unknown | 12 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 33 | 27% |
| Medicine and Dentistry | 18 | 15% |
| Psychology | 11 | 9% |
| Neuroscience | 9 | 7% |
| Biochemistry, Genetics and Molecular Biology | 6 | 5% |
| Other | 24 | 20% |
| Unknown | 21 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 40. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 February 2021.
All research outputs
#1,007,404
of 25,199,243 outputs
Outputs from Naunyn-Schmiedeberg's Archives of Pharmacology
#12
of 1,965 outputs
Outputs of similar age
#10,262
of 250,095 outputs
Outputs of similar age from Naunyn-Schmiedeberg's Archives of Pharmacology
#2
of 14 outputs
Altmetric has tracked 25,199,243 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,965 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 99% of its peers.
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We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.