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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao International journa...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
International journal of clinical monitoring and computing
Article . 1986 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Learning statistical methods

Authors: N L, Pace;

Learning statistical methods

Abstract

Since at least 1951 anesthesia journals have called for a more rigorous application of statistical methods in research reports. This appeal for statistical excellence actually applies to the researcher, to the clinician journal reader, and to the editor. Thirty five years ago the obligations of these three groups was made clear in an unsigned editorial in Anesthesiology; there is now a widespread consensus on these responsibilities. The researcher must create valid science. The clinician reader must bring sufficient intellectual skills to understand a journal article; using these skills the reader must critique the research report to judge its applicability to his patients. The editor must decline manuscripts showing poor or absent application of the scientific method, experimental design, and statistical analysis. Though the editors continue to exhort further improvements, even a casual perusal of their journals demonstrates a tremendous improvement in the handling of numeric data over the last four decades. With the increasing sophistication of statistical methods in journals, the reader must continue to expand his statistical understanding. In this short review, a few highlights of statistical methods useful either in planning and accomplishing a research project or in reading a research report will be discussed; these include the planning of a study design, data collection, data analysis, and interpretation of the research. Comments about using these concepts to better understand a research article will be included. Also included will be an annotated reading list for further study and reference. Mathematical formulas have been avoided as much as possible. Actual use of statistics requires use of equations which can be found in the books of the reading list.

Related Organizations
Keywords

Biometry, Education, Medical, Research Design, Data Collection, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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