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Shallow entangled circuits for quantum time series prediction on IBM devices. [PDF]
Sci RepLaskar MR, Goel R.
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Parametric Statistical Uncertainty Relations and Parametric Statistical Fundamental Equations
Annals of the Institute of Statistical Mathematics, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Statistical parametric mapping
2003This chapter deals with the experimental design and analysis of functional brain imaging studies. It considers the neurobiological motivations for different designs and describes some standard approaches, developed to analyse the ensuing data. Functional neuroimaging (positron emission tomography - PET and functional magnetic resonance imaging fMRI ...
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Non-parametric Statistical Methods
1987Basic statistics and econometrics courses stress methods based on assuming that the data or error term in regression models follow the normal distribution. Indeed, the efficiency of least squares estimates relies on the assumption of normality. In order to lessen the dependence of statistical inference on that assumption statisticians developed methods
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2018
Chapter 9 provides an introduction to statistical testing,alongside the most common parametric tests. It reviews the basis of hypothesis testing while highlighting important concepts such as chance, bias, and confounding. Additionally, this chapter discusses fundamental topics in basic statistics, including p-value, type I and type II errors, alpha (α)
Ben M. W. Illigens +3 more
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Chapter 9 provides an introduction to statistical testing,alongside the most common parametric tests. It reviews the basis of hypothesis testing while highlighting important concepts such as chance, bias, and confounding. Additionally, this chapter discusses fundamental topics in basic statistics, including p-value, type I and type II errors, alpha (α)
Ben M. W. Illigens +3 more
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2012
Beginning statistics students are usually introduced to what are called “parametric” statistics methods. Those methods utilize “models” of score distributions such as the normal (Gaussian) distribution, Poisson distribution, binomial distribution, etc.
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Beginning statistics students are usually introduced to what are called “parametric” statistics methods. Those methods utilize “models” of score distributions such as the normal (Gaussian) distribution, Poisson distribution, binomial distribution, etc.
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Parametric Statistical Inference
1996Abstract Inference involves drawing conclusions about some general phenomenon from limited empirical observations in the face of random variability. In a scientific context, the general must include the completely unforeseen if all possibilities are to be considered.
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