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Statistical hypothesis testing
BMJ, 2010A randomised controlled trial evaluated the cost and efficacy of community leg ulcer clinics that used four layer compression bandaging. The control treatment was provision of usual care by district nurses.1 Over the 12 months of follow-up, ulcers healed more quickly in the clinic group than in the control group (P=0.03).
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Testing a Statistical Hypothesis
2014This chapter deals with parametric test theory for a sample of independent and identically distributed observables. First, we introduce basic notions like null hypothesis, alternative hypothesis, errors of the first and of the second kind, significance level, and power.
Vladimir Spokoiny, Thorsten Dickhaus
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Statistical power in testing a hypothesis
The Journal of Bone and Joint Surgery. British volume, 2010In comparing or assessing methods of treatment it is vital that the appropriate number of patients is selected in order to ensure that the conclusions drawn are statistically viable. This annotation describes the relevance of a statistical power analysis in the context of hypothesis testing to the determination of the optimal sample size of a study ...
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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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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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Statistical Hypothesis Testing
2016In this chapter, hypothesis testing, which is another important method of statistical inference, is introduced. In the initial sections, the general guidelines for constructing hypotheses tests and the logic behind them are outlined. Then, the most common tests for normal populations are described and exemplified.
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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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Statistical Hypothesis Testing
2019This chapter describes an actual statistical hypothesis test using 10 years of pool data from a standard scoring pool. D. J. Breiter and B. P. Carlin referred to the “time-honored method of multiple pool entries.” They suggested the heuristic of using multiple entries from different strategies for optimizing brackets for submission to pools with upset ...
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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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