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The physicist Ernest Rutherford said, "If your experiment needs statistics, you ought to have done a better experiment." Although this aphorism remains true for much of today's research in cell biology, a basic understanding of statistics can be useful to cell biologists to help in monitoring the conduct of their experiments, in interpreting the results, in presenting them in publications, and when critically evaluating research by others. However, training in statistics is often focused on the sophisticated needs of clinical researchers, psychologists, and epidemiologists, whose conclusions depend wholly on statistics, rather than the practical needs of cell biologists, whose experiments often provide evidence that is not statistical in nature. This review describes some of the basic statistical principles that may be of use to experimental biologists, but it does not cover the sophisticated statistics needed for papers that contain evidence of no other kind.

Original publication

DOI

10.1146/annurev-cellbio-100913-013303

Type

Journal article

Publication Date

2014

Volume

30

Pages

23 - 37

Keywords

error bar, p-value, replicate, standard deviation, standard error, Causality, Cell Biology, Data Interpretation, Statistical, Probability, Reproducibility of Results, Research Design, Statistical Distributions, Statistics as Topic