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Hypothesis testing, type I and type II errors
Industrial Psychiatry Journal, 2009 Hypothesis testing is an important activity of empirical research and evidence-based medicine. A well worked up hypothesis is half the answer to the research question.
Amitav Banerjee +4 more
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Hypothesis Testing with Finite Statistics
The Annals of Mathematical Statistics, 1969 Let $X_1, X_2, \cdots$ be a sequence of independent identically distributed random variables drawn according to a probability measure $\mathscr{P}$. The two-hypothesis testing problem $H_0: \mathscr{P} = \mathscr{P}_0 \operatorname{vs.} H_1: \mathscr{P} = \mathscr{P}_1$ is investigated under the constraint that the data must be summarized after each ...
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F1000ResearchFailure to reject a null-hypothesis may lead to erroneous conclusions regarding the absence of an association or inadequate statistical power. Because an estimate (and its variance) can never be exactly zero, traditional statistical tests cannot ...
Amand Schmidt
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A Note on Statistical Hypothesis Testing: Probabilifying Modus Tollens Invalidates Its Force? Not True! [PDF]
Educ Psychol Meas, 2023 Widaman KF.
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Beyond P-Value-Obsession: When are Statistical Hypothesis Tests Required and Appropriate?
, 2022 Anne Margarian
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Statistical inference and statistical learning in economic research – selected challenges
EkonomistaThis paper presents the main trends and the most important challenges related to the use of classical and modern statistical methods in economic research.
Krzysztof Jajuga +2 more
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Understanding Statistical Testing
SAGE Open, 2015 Statistical hypothesis testing is common in research, but a conventional understanding sometimes leads to mistaken application and misinterpretation.
Peter J. Veazie
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Interpreting Results from Statistical Hypothesis Testing: Understanding the Appropriate P-value. [PDF]
Phys Ther Res, 2022 Tsushima E.
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Statistical significance and statistical power in hypothesis testing [PDF]
Journal of Orthopaedic Research, 1990 AbstractExperimental design requires estimation of the sample size required to produce a meaningful conclusion. Often, experimental results are performed with sample sizes which are inappropriate to adequately support the conclusions made. In this paper, two factors which are involved in sample size estimation are detailed—namely type I (α) and type II
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A Pragmatic Approach to Statistical Testing and Estimation (PASTE)
Health Professions Education, 2018 The p-value has dominated research in education and related fields and a statistically non-significant p-value is quite commonly interpreted as ‘confirming’ the null hypothesis (H0) of ‘equivalence’.
Jimmie Leppink
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