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The Logic of the Statistical Hypothesis Test
American Journal of EEG Technology, 1994ABSTRACT.This paper explains in simple language the logic of the statistical hypothesis test. Described are such concepts as sample and population, Type I and Type II errors (false positives and false negatives), power, level of confidence, and one- and two-tailed tests. A Glossary with definitions is provided at the end.
Michael Cavallaro, Linda Fidell
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Introduction to Inferential Statistics and Hypothesis Testing
Journal of the American Academy of Child & Adolescent Psychiatry, 2000When performing research, rarely are we able to work with an entire population of individuals. Instead, we usually test our treatment or intervention on a sample of individuals from the population. It is hoped that, if our treatment is successful, we can infer that the results from our sample apply to the population of interest.
Robert J. Harmon +2 more
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Fuzzy statistics: hypothesis testing
Soft Computing, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Understanding statistical hypothesis tests and power
Medical Journal of Australia, 2017Medical researchers often attempt to understand whether a risk factor is involved in the aetiology of disease or whether an intervention reduces disease; this has been the subject of another article in this series.1 We typically do this by proposing scientific hypotheses from which testable statistical hypotheses can be developed.
Christopher Oldmeadow +4 more
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A New Statistic for Bayesian Hypothesis Testing
Econometrics and Statistics, 2023Abstract A new Bayesian–inspired statistic for hypothesis testing is proposed which compares two posterior distributions; the observed posterior and the expected posterior under the null model. The Kullback–Leibler divergence between the two posterior distributions yields a test statistic which can be interpreted as a penalized log–Bayes factor with ...
Stephen G. Walker, Su Chen
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Hypothesis Testing and Statistics
2016Every quantity that is estimated from the data, such as the mean or the variance of a Gaussian variable, is subject to statistical fluctuations of the measurements. For this reason they are referred to as a statistics. If a different sample of measurements is collected, statistical fluctuations will certainly give rise to a different set of ...
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Alternatives to statistical hypothesis testing in ecology: a guide to self teaching.
Ecological Applications, 2006Statistical methods emphasizing formal hypothesis testing have dominated the analyses used by ecologists to gain insight from data. Here, we review alternatives to hypothesis testing including techniques for parameter estimation and model selection using
N., Thompson Hobbs, R. Hilborn
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Statistical hypothesis testing in biology: a contradiction in terms.
Journal of Economic Entomology, 1986We respond to the preceding article by Perry (J. Econ. Entomol. 79: 1149–1155) concerning the subject of hypothesis testing and meaningful presentation of statistical analyses. We agree with Perry that indiscriminate use of statistical hypothesis testing
Davy Jones, Norman Matloff
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Hypothesis Statement and Statistical Testing: A Tutorial
BOHR International Journal of Operations Management Research and Practices, 2022Many researchers and beginners in social research have several dilemmas and confusion in their mind about hypothesis statement and statistical testing of hypotheses. A distinction between the research hypothesis and statistical hypotheses, and understanding the limitations of the historically used null hypothesis statistical testing, is useful in ...
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Optimal multiple quantum statistical hypothesis testing
, 1975This paper is concerned with the problem of optimal M-alternative determination of quantum statistical states. A review of newest achievement of solving this problem is given.
V. Belavkin
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