Titlebook: Analysis of Neural Data; Robert E. Kass,Uri T. Eden,Emery N. Brown Book 2014 Springer Science+Business Media New York 2014 Data Analysis f

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Dimensionsanalyse in der Str?mungslehreal models introduce probability distributions to describe the variation due to noise, and thereby achieve quantitative expressions of knowledge about the signal—a process we will describe more fully in Chapters?. and ..

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,Effizienz der Π-Theorem Methodik, of maximum likelihood provides a better solution. How do we know this? In general, how should alternative methods of estimation be compared? In this chapter we lay out a series of principles that serve as guides to practice.

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https://doi.org/10.1007/978-3-658-20807-3 has an obvious limitation: it assumes the predictive relationship is, on average, linear. In addition, in its standard form it assumes that the noise contributions are homogeneous and follow, roughly, a normal distribution.

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Colin Jones,Mike Jenks,Glen BramleyData analysis involves both manipulation, via formulas and computations, and interpretation of the results. During the period immediately following World War II, particularly in the United States, statistical theory was consumed with the logic of statistical inference and decision-making. Against this backdrop, John Tukey revolted.

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Venetia Brown,Sheila CunninghamProbability is a rich and beautiful subject, a discipline unto itself. Its origins were concerned primarily with games of chance, and many lectures on elementary probability theory still contain references to dice, playing cards, and coin flips. These lottery-style scenarios remain useful because they are evocative and easy to understand.

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,Einführung in die Dimensionsanalyse,In most experimental settings data are collected simultaneously on many variables, and the statistical modeling problem is to describe their . variation, meaning their tendency to vary together.

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Dimensionsanalyse und hardware-Modelle,One of the great ideas in data analysis is to base probability statements on large-sample approximations, which are often easy to obtain either analytically or numerically.

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