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Books on the topic 'Inferenza'

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Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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1

Interazione e inferenza: Epistemologia scientifica ispirata al pensiero di Ch.S. Peirce. Roma: Gregorian & Biblical Press, 2010.

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2

Tuzet, Giovanni. La prima inferenza: L'abduzione di C. S. Peirce fra scienza e diritto. Torino: G. Giappichelli, 2006.

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Tuzet, Giovanni. La prima inferenza: L'abduzione di C. S. Peirce fra scienza e diritto. Torino: G. Giappichelli, 2006.

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4

Sandrini, Maria Grazia. L' inferenza induttiva in Bayes e in Fisher: Due metodi a confronto in un saggio storico-critico di epistemologia e metodologia scientifica. Milano, Italy: F. Angeli, 1987.

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5

INFERENCE. [Place of publication not identified]: RINGWOOD Publishing, 2019.

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6

Bibel, Wolfgang. Wissensrepräsentation und Inferenz. Wiesbaden: Vieweg+Teubner Verlag, 1993. http://dx.doi.org/10.1007/978-3-322-86814-5.

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7

Statistical inference. Chestnut Hill, MA: Epidemiology Resources Inc., 1990.

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8

T, Jolliffe I., and Jones Byron 1951-, eds. Statistical inference. Oxford: Oxford University Press, 2002.

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9

Bazett, Trefor. Bayesian Inference. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95792-6.

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10

Wieczorek, Wojciech. Grammatical Inference. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46801-3.

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11

Schölkopf, Bernhard, Zhiyuan Luo, and Vladimir Vovk, eds. Empirical Inference. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41136-6.

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12

Bromek, Tadeusz, and Elżbieta Pleszczyńska, eds. Statistical Inference. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0575-7.

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13

Harney, Hanns Ludwig. Bayesian Inference. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41644-1.

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14

Panik, Michael J. Statistical Inference. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118309773.

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15

Honavar, Vasant, and Giora Slutzki, eds. Grammatical Inference. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0054058.

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16

Pouly, Marc, and Jürg Kohlas. Generic Inference. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118010877.

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17

Harney, Hanns L. Bayesian Inference. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-06006-3.

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18

Verbelen, Tim, Pablo Lanillos, Christopher L. Buckley, and Cedric De Boom, eds. Active Inference. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64919-7.

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19

L, Berger Roger, ed. Statistical Inference. 2nd ed. Australia: Thomson Learning, 2002.

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20

Lee, Won Don. Probabilistic inference. Urbana, Ill: Dept. of Computer Science, University of Illinois at Urbana-Champaign, 1986.

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21

Garthwaite, Paul H. Statistical inference. 2nd ed. Oxford: Oxford University Press, 2002.

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22

J, Rothman Kenneth, Lanes Stephan F, and Society for Epidemiologic Research (U.S.). Meeting, eds. Causal inference. Chestnut Hill, MA: Epidemiology Resources, 1988.

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23

Oakes, Michael W. Statistical inference. Chestnut Hill, MA: Epidemiology Resources Inc., 1990.

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24

Harold, Jeffreys. Scientific inference. Cambridge: Cambridge University Press, 2007.

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25

Tan, W. Y., and N. Balakrishnan, eds. Robust inference. New York, USA: M. Dekker, 1986.

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26

Silvey, S. D. Statistical inference. London: Chapman and Hall, 1988.

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27

L, Berger Roger, ed. Statistical inference. Pacific Grove, Calif: Brooks/Cole Pub. Co., 1990.

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28

Garthwaite, Paul H. Statistical inference. London: Prentice Hall, 1995.

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29

1963-, Polson Nicholas G., and Tiao George C. 1933-, eds. Bayesian inference. Aldershot, Hants, England: E. Elgar Pub. Co., 1995.

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30

Inferenza Statistica. Springer Verlag, 1992.

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31

Malacrida, Simone. Esercizi di matematica: Inferenza statistica. CreateSpace Independent Publishing Platform, 2016.

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32

Capaccioli, David. inferenza Statistica Non é (più) un Problema. Independently Published, 2022.

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33

Azzalini, A. Inferenza Statistica: Un'Introduzione Basata Sul Concetto Di Verosimiglianza (Springer-Collana Di Stastica). Springer-Verlag, 1992.

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34

Azzalini, A. Inferenza statistica: Una presentazione basata sul concetto di verosimiglianza (UNITEXT / Collana di Statistica e Probabilità Applicata). 2nd ed. Springer, 2004.

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35

Ippoliti, Emiliano. Inferenze Ampliative. Lulu Press, Inc., 2008.

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36

Schlittgen, Rainer. Statistische Inferenz. de Gruyter GmbH, Walter, 1995.

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37

Schlittgen, Rainer. Statistische Inferenz. de Gruyter GmbH, Walter, 2018.

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38

Sainsbury, Mark. Inference. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198803348.003.0006.

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Display theory predicts that no inferential relations among attitude attributions are based on the logical or semantic properties of the expressions in attribution complements. This chapter shows various ways in which there may be an illusion that such relations obtain. One common basis for the illusion is that we implicitly appeal to psychological facts. Since there is no reason to think these are necessary, the inferences are not truth preserving of necessity, even if they generally have true conclusions when they have true premises. They are examples of “plausible reasoning”. Wanting and fearing are discussed in detail as potential sources of the apparently inferential phenomena.

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39

Mukhyopadhyay, Pritam. Inference. Independently Published, 2019.

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40

Patel, Shantilal R. Statistical Inference: Classical and Bayesian Inference. I.K. International Publishing House Pvt. Ltd, 2022.

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41

Unknown. Robust Inference. Elsevier Science & Technology Books, 1997.

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42

Silvey, S. D. Statistical Inference. CRC Press LLC, 2017.

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43

Pouly, Marc, and Juerg Kohlas. Generic Inference. Wiley & Sons, Incorporated, John, 2011.

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44

Ackermann, Robert. Nondeductive Inference. Taylor & Francis Group, 2019.

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45

Panik, Michael J. Statistical Inference. Wiley & Sons, Incorporated, John, 2012.

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46

Teng, Choh Man, and Kyburg Henry E. Jr. Uncertain Inference. Cambridge University Press, 2009.

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47

Gelman, Andrew, and Deborah Nolan. Statistical inference. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198785699.003.0009.

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This chapter begins with a very successful demonstration that illustrates many of the general principles of statistical inference, including estimation, bias, and the concept of the sampling distribution. Students each take a “random” sample of different size candies, weigh them, and estimate the total weight of all candies. Then various demonstrations and examples are presented that take the students on the transition from probability to hypothesis testing, confidence intervals, and more advanced concepts such as statistical power and multiple comparisons. These activities include use an inflatable globe, short-term memory test, first digits of street addresses, and simulated student IQs.

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48

Govindarajulu, Z. Nonparametric Inference. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/6244.

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49

Golan, Amos. Rational Inference. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199349524.003.0002.

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In this chapter I present arguments for the use of info-metrics as a fundamental framework for rational inference. The chapter consists of two interdependent parts. In the first I provide the framework for rational inference, which involves the use of a specific decision function to achieve the desired inference. In the second part I summarize four sets of axioms to justify the decision function argued for in the first part. All axioms lead to the same decision function: the entropy function of Boltzmann, Gibbs, and Shannon. In this chapter I emphasize underdetermined problems and problems of insufficient information, but I also discuss inference based on information resulting from repeated independent experiments. The same entropy function is identified in each case, as well as the desired decision function.

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50

Ackermann, Robert. Nondeductive Inference. Routledge, 2019. http://dx.doi.org/10.4324/9780367853907.

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