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Teleology --- Finalité --- Aristotle --- Design in natural phenomena, Study of --- Final cause --- Philosophy --- Causation --- Evolution --- Necessity (Philosophy) --- Aristoteles. --- Aristoteles --- Aristote --- Aristotile --- Finalité --- Aristotle. --- Arisṭāṭṭil --- Aristo, --- Aristotel --- Aristotele --- Aristóteles, --- Aristòtil --- Arisṭū --- Arisṭūṭālīs --- Arisutoteresu --- Arystoteles --- Ya-li-shih-to-te --- Ya-li-ssu-to-te --- Yalishiduode --- Yalisiduode --- Ἀριστοτέλης --- Αριστοτέλης --- Аристотел --- ארסטו --- אריםטו --- אריסטו --- אריסטוטלס --- אריסטוטלוס --- אריסטוטליס --- أرسطاطاليس --- أرسططاليس --- أرسطو --- أرسطوطالس --- أرسطوطاليس --- ابن رشد --- اريسطو --- Pseudo Aristotele --- Pseudo-Aristotle --- アリストテレス
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David A. Freedman presents here a definitive synthesis of his approach to causal inference in the social sciences. He explores the foundations and limitations of statistical modeling, illustrating basic arguments with examples from political science, public policy, law, and epidemiology. Freedman maintains that many new technical approaches to statistical modeling constitute not progress, but regress. Instead, he advocates a 'shoe leather' methodology, which exploits natural variation to mitigate confounding and relies on intimate knowledge of the subject matter to develop meticulous research designs and eliminate rival explanations. When Freedman first enunciated this position, he was met with scepticism, in part because it was hard to believe that a mathematical statistician of his stature would favor 'low-tech' approaches. But the tide is turning. Many social scientists now agree that statistical technique cannot substitute for good research design and subject matter knowledge. This book offers an integrated presentation of Freedman's views.
Causation. --- Linear models (Statistics). --- Social sciences --- Statistical methods. --- Linear models (Statistics) --- Causation --- Sciences sociales --- Modèles linéaires (Statistique) --- Causalité --- Statistical methods --- Méthodes statistiques --- #SBIB:303H510 --- #SBIB:303H520 --- 303.6 --- AA / International- internationaal --- Models, Linear (Statistics) --- Mathematical models --- Mathematical statistics --- Statistics --- Causality --- Cause and effect --- Effect and cause --- Final cause --- Beginning --- God --- Metaphysics --- Philosophy --- Necessity (Philosophy) --- Teleology --- Methoden sociale wetenschappen: statistische technieken, algemeen --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Raming : theorie (wiskundige statistiek). Bayesian analysis and inference
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The anti-causal prophecies of last century have been disproved. Causality is neither a ‘relic of a bygone’ nor ‘another fetish of modern science’; it still occupies a large part of the current debate in philosophy and the sciences. This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, not of regularity nor invariance, thus breaking down the dominant Humean paradigm. The notion of variation is shown to be embedded in the scheme of reasoning behind various causal models: e.g. Rubin’s model, contingency tables, and multilevel analysis. It is also shown to be latent—yet fundamental—in many philosophical accounts. Moreover, it has significant consequences for methodological issues: the warranty of the causal interpretation of causal models, the levels of causation, the characterisation of mechanisms, and the interpretation of probability. This book offers a novel philosophical and methodological approach to causal reasoning in causal modelling and provides the reader with the tools to be up to date about various issues causality rises in social science. "Dr. Federica Russo's book is a very valuable addition to a small number of relevant publications on causality and causal modelling in the social sciences viewed from a philosophical approach".(Prof. Guillaume Wunsch, Institute of Demography, University of Louvain, Belgium).
Causation. --- Probabilities. --- Social sciences -- Philosophy. --- Social Sciences --- Social Sciences - General --- Social sciences --- Social philosophy --- Social theory --- Causality --- Cause and effect --- Effect and cause --- Final cause --- Philosophy. --- Social sciences. --- Philosophy and social sciences. --- Statistics. --- Economics. --- Management science. --- Population. --- Demography. --- Social Sciences. --- Methodology of the Social Sciences. --- Economics, general. --- Philosophy of the Social Sciences. --- Population Economics. --- Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. --- Statistics for Social Science, Behavioral Science, Education, Public Policy, and Law. --- Historical demography --- Population --- Vital statistics --- Human population --- Human populations --- Population growth --- Populations, Human --- Economics --- Human ecology --- Sociology --- Demography --- Malthusianism --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Economic theory --- Political economy --- Economic man --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Social sciences and philosophy --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Beginning --- God --- Metaphysics --- Philosophy --- Necessity (Philosophy) --- Teleology --- Statistics for Social Sciences, Humanities, Law. --- Methodology. --- Statistics .
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