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Books on the topic 'Inferenza'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

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

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

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3

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. F. Angeli, 1987.

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4

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

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5

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

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6

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

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7

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

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8

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

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9

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

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10

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

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11

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

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12

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

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13

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

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14

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

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15

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

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16

L, Berger Roger, ed. Statistical inference. Brooks/Cole Pub. Co., 1990.

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17

Tan, W. Y., and N. Balakrishnan, eds. Robust inference. M. Dekker, 1986.

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18

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

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19

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

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20

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

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21

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

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22

Oakes, Michael W. Statistical inference. Epidemiology Resources Inc., 1990.

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23

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

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24

Buckley, Christopher L., Daniela Cialfi, Pablo Lanillos, et al., eds. Active Inference. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-47958-8.

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25

Buckley, Christopher L., Daniela Cialfi, Pablo Lanillos, et al., eds. Active Inference. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28719-0.

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26

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

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27

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

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28

Inferenza Statistica. Springer Verlag, 1992.

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29

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

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30

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

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31

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

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32

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

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33

Elettori in movimento: Nuove tecniche di inferenza ecologica per lo studio dei flussi elettorali. Polistampa, 2008.

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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, 2018.

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37

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

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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 fe

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39

INFERENCE. RINGWOOD Publishing, 2019.

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40

Mukhyopadhyay, Pritam. Inference. Independently Published, 2019.

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41

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

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42

Wissensrepräsentation und Inferenz: Eine grundlegende Einführung. Vieweg+Teubner Verlag, 1993.

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43

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

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44

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

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45

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

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46

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

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47

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

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48

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 infl

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49

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

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50

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

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