Accuracy when inferential statistics are used as measurement tools

BMC Research Notes

Volumn 9, Issue 1, 2016, Pages

  Bradley, Michael T ^a   Brand, Andrew ^b  

^a UNIVERSITY OF NEW BRUNSWICK   (Canada)

^b BANGOR UNIVERSITY   (United Kingdom)

Author keywords

Accuracy; Measurement; Neyman and Pearson; Probabilities; Type 1 errors; Type 2 errors

Indexed keywords

MONTE CARLO METHOD; PROBABILITY; PROCEDURES; REPRODUCIBILITY; SCIENCE; STATISTICAL MODEL; STATISTICS; STATISTICS AND NUMERICAL DATA;

MODELS, STATISTICAL; MONTE CARLO METHOD; PROBABILITY; REPRODUCIBILITY OF RESULTS; SCIENCE; STATISTICS AS TOPIC;

EID: 84964686308     PISSN: None     EISSN: 17560500     Source Type: Journal    
DOI: 10.1186/s13104-016-2045-z     Document Type: Article

References (4)

1. Neyman J, Pearson ES. The testing of statistical hypotheses in relation to probabilities a priori. Proc Camb Philos Soc. 1933;29:492-510.
2. Wald A. Statistical decision functions. New York: Wiley; 1950.
3. Cohen J. Statistical power analysis for the behavioral sciences. New York: Academic Press; 1977.
4. Fisher RA. Statistical methods and scientific inference. 3rd ed. New York: Hafner; 1973.