Hypothesis-Testing Improves the Predicted Reliability of Neuroscience Research

Be, Alger

doi:10.1101/537365

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…These studies are often statistically underpowered and therefore even positive results obtained in these conditions should not be considered sufficient evidence to draw solid conclusions. Importantly, this need is not exclusive to BMI but also pertains to closely related fields like neuroscience and cognitive psychology [49,50]. Nonetheless, specific characteristics and constraints of BMI scenarios make this approach more difficult.…”

Section: At a Methodological Levelmentioning

confidence: 99%

Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI) research

Lotte

Jeunet

Chavarriaga

et al. 2019

Brain-Computer Interfaces

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Results that do not confirm expectations are generally referred to as "negative" results. While essential for scientific progress, they are too rarely reported in the literature-Brain-Machine Interface (BMI) research is no exception. This led us to organize a workshop on BMI negative results during the 2018 International BCI meeting. The outcomes of this workshop are reported herein. First, we demonstrate why (valid) negative results are useful, and even necessary for BMIs. These results can be used to confirm or disprove current BMI knowledge, or to refine current theories. Second, we provide concrete examples of such useful negative results, including the limits in BMI-control for complete locked-in users and predictors of motor imagery BMI performances. Finally, we suggest levers to promote the diffusion of (valid) BMI negative results, e.g., promoting hypothesis-driven research using valid statistical tools, organizing special issues dedicated to BMI negative results, or convincing institutions and editors that negative results are valuable.

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Section: At a Methodological Levelmentioning

confidence: 99%

Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI) research

Lotte

Jeunet

Chavarriaga

et al. 2019

Brain-Computer Interfaces

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“…They showed how this approach can provide rigorous interim monitoring of the trials and efficient assessment of the durability of vaccine efficacy. They presented a simple and rigorous framework to consider the totality of evidence when evaluating the benefit of a COVID-19 vaccine in reducing SARS-CoV-2 infection, COVID-19, and severe COVID-19 [8].…”

Section: Literature Surveymentioning

confidence: 99%

Treatment Analysis of COVID-19 Patient with Age Factor Using Chi Square Test

Shekhar¹,

Patel²

2022

IJRASET

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A hypothesis provides the map that guides and expedites the exploration of the phenomena under consideration. A hypothesis pin points the problem.. The hypothesis provides the investigator with the most efficient instrument for exploring and explaining the unknown facts. A hypothesis provides the framework for drawing conclusions. These hypotheses simulate the investigator for further research studies. In this paper used Hypothesis testing with chi square test to analysis COVID -19 Patient treatment and age factors. Using Hypothesis testing we want to check State for the null and alternative hypotheses. The null hypotheses say that COVID - 19 patient treatment and age factors are related with each other and alternate hypothesis say that there is no relationship exist COVID -19 patient treatment and age factors. We have taken more 1000 COVID -19 infected patient treatment with age factor. We select a random sample of 300 and 400 patient and by experimental analysis we found that the age is not a factor for required treatment. COIVD-19 infected patient can we any of the age group and required treatment are dependent on the immunity system of the patient. Keywords: Hypothesis, Patient COVID-19, Treatment, Age Factor, Immunity

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Hypothesis-Testing Improves the Predicted Reliability of Neuroscience Research

Cited by 2 publications

References 8 publications

Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI) research

Turning negative into positives! Exploiting ‘negative’ results in Brain–Machine Interface (BMI) research

Treatment Analysis of COVID-19 Patient with Age Factor Using Chi Square Test

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