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Statistical methods in microbiology
Author(s) -
D M Ilstrup
Publication year - 1990
Publication title -
clinical microbiology reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.177
H-Index - 282
eISSN - 1070-6305
pISSN - 0893-8512
DOI - 10.1128/cmr.3.3.219
Subject(s) - statistician , blinding , statistical analysis , set (abstract data type) , control (management) , psychology , statistical hypothesis testing , nothing , computer science , data science , statistics , medicine , epistemology , mathematics , artificial intelligence , clinical trial , philosophy , pathology , programming language
Statistical methodology is viewed by the average laboratory scientist, or physician, sometimes with fear and trepidation, occasionally with loathing, and seldom with fondness. Statistics may never be loved by the medical community, but it does not have to be hated by them. It is true that statistical science is sometimes highly mathematical, always philosophical, and occasionally obtuse, but for the majority of medical studies it can be made palatable. The goal of this article has been to outline a finite set of methods of analysis that investigators should choose based on the nature of the variable being studied and the design of the experiment. The reader is encouraged to seek the advice of a professional statistician when there is any doubt about the appropriate method of analysis. A statistician can also help the investigator with problems that have nothing to do with statistical tests, such as quality control, choice of response variable and comparison groups, randomization, and blinding of assessment of response variables.

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