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Basic Elements of Bayesian Analysis
Basic Elements of Bayesian Analysis

... Basic Elements of Bayesian Analysis In a frequentist analysis, one chooses a model (likelihood function) for the available data, and then either calculates a p-value (which tells you how unusual your data would be, assuming your null hypothesis is exactly true), or calculates a confidence interval. ...
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pptx - University of Pittsburgh

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... Notice that the drop-down box gives two choices for the data. Note that the “Graphs” button is only available when we have the individual data values because we could not produce a graph of the data from just the value from the summarized data. One or more samples, each in a column ...
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Foundations of statistics

Foundations of statistics is the usual name for the epistemological debate in statistics over how one should conduct inductive inference from data. Among the issues considered in statistical inference are the question of Bayesian inference versus frequentist inference, the distinction between Fisher's ""significance testing"" and Neyman-Pearson ""hypothesis testing"", and whether the likelihood principle should be followed. Some of these issues have been debated for up to 200 years without resolution.Bandyopadhyay & Forster describe four statistical paradigms: ""(1) classical statistics or error statistics, (ii) Bayesian statistics, (iii) likelihood-based statistics, and (iv) the Akaikean-Information Criterion-based statistics"".Savage's text Foundations of Statistics has been cited over 10000 times on Google Scholar. It tells the following.It is unanimously agreed that statistics depends somehow on probability. But, as to what probability is and how it is connected with statistics, there has seldom been such complete disagreement and breakdown of communication since the Tower of Babel. Doubtless, much of the disagreement is merely terminological and would disappear under sufficiently sharp analysis.
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