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1	Toward Error-Statistical Principles of Evidence in Statistical Inference Jinn, Nicole Mee-Hyaang 02 June 2014 (has links) The context for this research is statistical inference, the process of making predictions or inferences about a population from observation and analyses of a sample. In this context, many researchers want to grasp what inferences can be made that are valid, in the sense of being able to uphold or justify by argument or evidence. Another pressing question among users of statistical methods is: how can spurious relationships be distinguished from genuine ones? Underlying both of these issues is the concept of evidence. In response to these (and similar) questions, two questions I work on in this essay are: (1) what is a genuine principle of evidence? and (2) do error probabilities have more than a long-run role? Concisely, I propose that felicitous genuine principles of evidence should provide concrete guidelines on precisely how to examine error probabilities, with respect to a test's aptitude for unmasking pertinent errors, which leads to establishing sound interpretations of results from statistical techniques. The starting point for my definition of genuine principles of evidence is Allan Birnbaum's confidence concept, an attempt to control misleading interpretations. However, Birnbaum's confidence concept is inadequate for interpreting statistical evidence, because using only pre-data error probabilities would not pick up on a test's ability to detect a discrepancy of interest (e.g., "even if the discrepancy exists" with respect to the actual outcome. Instead, I argue that Deborah Mayo's severity assessment is the most suitable characterization of evidence based on my definition of genuine principles of evidence. / Master of Arts Statistical Inference Evidential/Inferential Interpretations Evidence Sampling distributions Likelihood Principle Bayesian methods Error Statistics Frequentist methods Philosophy of Statistics Statistics Education
2	Naturalism & Objectivity: Methods and Meta-methods Miller, Jean Anne 19 August 2011 (has links) The error statistical account provides a basic account of evidence and inference. Formally, the approach is a re-interpretation of standard frequentist (Fisherian, Neyman-Pearson) statistics. Informally, it gives an account of inductive inference based on arguing from error, an analog of frequentist statistics, which keeps the concept of error probabilities central to the evaluation of inferences and evidence. Error statistical work at present tends to remain distinct from other approaches of naturalism and social epistemology in philosophy of science and, more generally, Science and Technology Studies (STS). My goal is to employ the error statistical program in order to address a number of problems to approaches in philosophy of science, which fall under two broad headings: (1) naturalistic philosophy of science and (2) social epistemology. The naturalistic approaches that I am interested in looking at seek to provide us with an account of scientific and meta-scientific methodologies that will avoid extreme skepticism, relativism and subjectivity and claim to teach us something about scientific inferences and evidence produced by experiments (broadly construed). I argue that these accounts fail to identify a satisfactory program for achieving those goals and; moreover, to the extent that they succeed it is by latching on to the more general principles and arguments from error statistics. In sum, I will apply the basic ideas from error statistics and use them to examine (and improve upon) an area to which they have not yet been applied, namely in assessing and pushing forward these interdisciplinary pursuits involving naturalistic philosophies of science that appeal to cognitive science, psychology, the scientific record and a variety of social epistemologies. / Ph. D. epistemology error statistics Giere Hurlbert micro-sociology of science minimal a priorism meta-methods methods Mayo Kitcher Latour Longino Collins relativism reflexivity replication social epistemologies relativism pseudo-replication philosophy of statistics misspecification testing naturalism new experimentalism normative naturalism objectivity philosophy of experiment philosophy of science

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Toward Error-Statistical Principles of Evidence in Statistical Inference

Naturalism & Objectivity: Methods and Meta-methods