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Gotowa bibliografia na temat „Combinatorial statistics”

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Data publikacji: 20 lipca 2024

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Artykuły w czasopismach na temat "Combinatorial statistics"

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Gerards, A. M. H., i A. W. J. Kolen. "Polyhedral Combinatorics in Combinatorial Optimization". Statistica Neerlandica 41, nr 1 (marzec 1987): 1–25. http://dx.doi.org/10.1111/j.1467-9574.1987.tb01168.x.

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Niven, R. K. "Combinatorial entropies and statistics". European Physical Journal B 70, nr 1 (16.05.2009): 49–63. http://dx.doi.org/10.1140/epjb/e2009-00168-5.

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Hansen, J. C. "Order statistics for random combinatorial structures". Advances in Applied Probability 24, nr 4 (grudzień 1992): 774. http://dx.doi.org/10.1017/s0001867800024836.

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Denise, Alain, i Rodica Simion. "Two combinatorial statistics on Dyck paths". Discrete Mathematics 137, nr 1-3 (styczeń 1995): 155–76. http://dx.doi.org/10.1016/0012-365x(93)e0147-v.

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Simion, Rodica. "Combinatorial statistics on non-crossing partitions". Journal of Combinatorial Theory, Series A 66, nr 2 (maj 1994): 270–301. http://dx.doi.org/10.1016/0097-3165(94)90066-3.

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Hansen, Jennie C. "Order statistics for decomposable combinatorial structures". Random Structures & Algorithms 5, nr 4 (październik 1994): 517–33. http://dx.doi.org/10.1002/rsa.3240050404.

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Calvin, James A., i Marshall Hall. "Combinatorial Theory." Journal of the American Statistical Association 82, nr 400 (grudzień 1987): 1197. http://dx.doi.org/10.2307/2289431.

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Bernabei, Maria Simonetta, i Horst Thaler. "Central Limit Theorem for Coloured Hard Dimers". Journal of Probability and Statistics 2010 (2010): 1–13. http://dx.doi.org/10.1155/2010/781681.

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We study the central limit theorem for a class of coloured graphs. This means that we investigate the limit behavior of certain random variables whose values are combinatorial parameters associated to these graphs. The techniques used at arriving this result comprise combinatorics, generating functions, and conditional expectations.
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SCHORK, MATTHIAS. "SOME ALGEBRAICAL, COMBINATORIAL AND ANALYTICAL PROPERTIES OF PARAGRASSMANN VARIABLES". International Journal of Modern Physics A 20, nr 20n21 (20.08.2005): 4797–819. http://dx.doi.org/10.1142/s0217751x05025127.

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Some algebraical, combinatorial and analytical aspects of paragrassmann variables are discussed. In particular, the similarity of the combinatorics involved with those of generalized exclusion statistics (Gentile's intermediate statistics) is stressed. It is shown that the dimensions of the algebras of generalized grassmann variables are related to generalized Fibonacci numbers. On the analytical side, some of the simplest differential equations are discussed and a suitably generalized Berezin integral as well as an associated delta-function are considered. Some remarks concerning a geometrical interpretation of recent results about fractional superconformal transformations involving generalized grassmann variables are given. Finally, a quantity related to the Witten index is discussed.
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Crane, Harry. "Combinatorial Lévy processes". Annals of Applied Probability 28, nr 1 (luty 2018): 285–339. http://dx.doi.org/10.1214/17-aap1306.

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Rozprawy doktorskie na temat "Combinatorial statistics"

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Ning, Michael Zhu. "Relational combinatorial optimisation". Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284507.

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Olsen, McCabe J. "HILBERT BASES, DESCENT STATISTICS, AND COMBINATORIAL SEMIGROUP ALGEBRAS". UKnowledge, 2018. https://uknowledge.uky.edu/math_etds/52.

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The broad topic of this dissertation is the study of algebraic structure arising from polyhedral geometric objects. There are three distinct topics covered over three main chapters. However, each of these topics are further linked by a connection to the Eulerian polynomials. Chapter 2 studies Euler-Mahonian identities arising from both the symmetric group and generalized permutation groups. Specifically, we study the algebraic structure of unit cube semigroup algebra using Gröbner basis methods to acquire these identities. Moreover, this serves as a bridge between previous methods involving polyhedral geometry and triangulations with descent bases methods arising in representation theory. In Chapter 3, the aim is to characterize Hilbert basis elements of certain 𝒔-lecture hall cones. In particular, the main focus is the classification of the Hilbert bases for the 1 mod 𝑘 cones and the 𝓁-sequence cones, both of which generalize a previous known result. Additionally, there is much broader characterization of Hilbert bases in dimension ≤ 4 for 𝒖-generated Gorenstein lecture hall cones. Finally, Chapter 4 focuses on certain algebraic and geometric properties of 𝒔-lecture hall polytopes. This consists of partial classification results for the Gorenstein property, the integer-decomposition property, and the existence of regular, unimodular triangulations.
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Quinn, Kathleen Anne Sara. "Combinatorial structures with applications to information theory". Thesis, Royal Holloway, University of London, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.261791.

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Marett, Richard Colin. "Neighbourhood search techniques for multi-objective combinatorial problems". Thesis, Lancaster University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296889.

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McShine, Lisa Maria. "Random sampling of combinatorial structures". Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/28771.

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Williams, Trevor K. "Combinatorial Games on Graphs". DigitalCommons@USU, 2017. https://digitalcommons.usu.edu/etd/6502.

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Combinatorial games are intriguing and have a tendency to engross students and lead them into a serious study of mathematics. The engaging nature of games is the basis for this thesis. Two combinatorial games along with some educational tools were developed in the pursuit of the solution of these games. The game of Nim is at least centuries old, possibly originating in China, but noted in the 16th century in European countries. It consists of several stacks of tokens, and two players alternate taking one or more tokens from one of the stacks, and the player who cannot make a move loses. The formal and intense study of Nim culminated in the celebrated Sprague-Grundy Theorem, which is now one of the centerpieces in the theory of impartial combinatorial games. We study a variation on Nim, played on a graph. Graph Nim, for which the theory of Sprague-Grundy does not provide a clear strategy, was originally developed at the University of Colorado Denver. Graph Nim was first played on graphs of three vertices. The winning strategy, and losing position, of three vertex Graph Nim has been discovered, but we will expand the game to four vertices and develop the winning strategies for four vertex Graph Nim. Graph Theory is a markedly visual field of mathematics. It is extremely useful for graph theorists and students to visualize the graphs they are studying. There exists software to visualize and analyze graphs, such as SAGE, but it is often extremely difficult to learn how use such programs. The tools in GeoGebra make pretty graphs, but there is no automated way to make a graph or analyze a graph that has been built. Fortunately GeoGebra allows the use of JavaScript in the creation of buttons which allow us to build useful Graph Theory tools in GeoGebra. We will discuss two applets we have created that can be used to help students learn some of the basics of Graph Theory. The game of thrones is a two-player impartial combinatorial game played on an oriented complete graph (or tournament) named after the popular fantasy book and TV series. The game of thrones relies on a special type of vertex called a king. A king is a vertex, k, in a tournament, T, which for all x in T either k beats x or there exists a vertex y such that k beats y and y beats x. Players take turns removing vertices from a given tournament until there is only one king left in the resulting tournament. The winning player is the one which makes the final move. We develop a winning position and classify those tournaments that are optimal for the first or second-moving player.
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Niese, Elizabeth M. "Combinatorial Properties of the Hilbert Series of Macdonald Polynomials". Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/26702.

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The original Macdonald polynomials $P_\mu$ form a basis for the vector space of symmetric functions which specializes to several of the common bases such as the monomial, Schur, and elementary bases. There are a number of different types of Macdonald polynomials obtained from the original $P_\mu$ through a combination of algebraic and plethystic transformations one of which is the modified Macdonald polynomial $\widetilde{H}_\mu$. In this dissertation, we study a certain specialization $\widetilde{F}_\mu(q,t)$ which is the coefficient of $x_1x_2 ... x_N$ in $\widetilde{H}_\mu$ and also the Hilbert series of the Garsia-Haiman module $M_\mu$. Haglund found a combinatorial formula expressing $\widetilde{F}_\mu$ as a sum of $n!$ objects weighted by two statistics. Using this formula we prove a $q,t$-analogue of the hook-length formula for hook shapes. We establish several new combinatorial operations on the fillings which generate $\widetilde{F}_\mu$. These operations are used to prove a series of recursions and divisibility properties for $\widetilde{F}_\mu$.
Ph. D.
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Hites, Romina. "Robustness and preferences in combinatorial optimization". Doctoral thesis, Universite Libre de Bruxelles, 2005. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210905.

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In this thesis, we study robust combinatorial problems with interval data. We introduce several new measures of robustness in response to the drawbacks of existing measures of robustness. The idea of these new measures is to ensure that the solutions are satisfactory for the decision maker in all scenarios, including the worst case scenario. Therefore, we have introduced a threshold over the worst case costs, in which above this threshold, solutions are no longer satisfactory for the decision maker. It is, however, important to consider other criteria than just the worst case.

Therefore, in each of these new measures, a second criteria is used to evaluate the performance of the solution in other scenarios such as the best case one.

We also study the robust deviation p-elements problem. In fact, we study when this solution is equal to the optimal solution in the scenario where the cost of each element is the midpoint of its corresponding interval.

Then, we finally formulate the robust combinatorial problem with interval data as a bicriteria problem. We also integrate the decision maker's preferences over certain types of solutions into the model. We propose a method that uses these preferences to find the set of solutions that are never preferred by any other solution. We call this set the final set.

We study the properties of the final sets from a coherence point of view and from a robust point of view. From a coherence point of view, we study necessary and sufficient conditions for the final set to be monotonic, for the corresponding preferences to be without cycles, and for the set to be stable.

Those that do not satisfy these properties are eliminated since we believe these properties to be essential. We also study other properties such as the transitivity of the preference and indifference relations and more. We note that many of our final sets are included in one another and some are even intersections of other final sets. From a robust point of view, we compare our final sets with different measures of robustness and with the first- and second-degree stochastic dominance. We show which sets contain all of these solutions and which only contain these types of solutions. Therefore, when the decision maker chooses his preferences to find the final set, he knows what types of solutions may or may not be in the set.

Lastly, we implement this method and apply it to the Robust Shortest Path Problem. We look at how this method performs using different types of randomly generated instances.


Doctorat en sciences, Orientation recherche opérationnelle
info:eu-repo/semantics/nonPublished

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Talebi, Mazraeh Shahi Mohammad Sadegh. "Minimizing Regret in Combinatorial Bandits and Reinforcement Learning". Doctoral thesis, KTH, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-219970.

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This thesis investigates sequential decision making tasks that fall in the framework of reinforcement learning (RL). These tasks involve a decision maker repeatedly interacting with an environment modeled by an unknown finite Markov decision process (MDP), who wishes to maximize a notion of reward accumulated during her experience. Her performance can be measured through the notion of regret, which compares her accumulated expected reward against that achieved by an oracle algorithm always following an optimal behavior. In order to maximize her accumulated reward, or equivalently to minimize the regret, she needs to face a trade-off between exploration and exploitation. The first part of this thesis investigates combinatorial multi-armed bandit (MAB) problems, which are RL problems whose state-space is a singleton. It also addresses some applications that can be cast as combinatorial MAB problems. The number of arms in such problems generically grows exponentially with the number of basic actions, but the rewards of various arms are correlated. Hence, the challenge in such problems is to exploit the underlying combinatorial structure.For these problems, we derive asymptotic (i.e., when the time horizon grows large) lower bounds on the regret of any admissible algorithm and investigate how these bounds scale with the dimension of the underlying combinatorial structure. We then propose several algorithms and provide finite-time analyses of their regret. The proposed algorithms efficiently exploit the structure of the problem, provide better performance guarantees than existing algorithms, and significantly outperform these algorithms in practice. The second part of the thesis concerns RL in an unknown and discrete MDP under the average-reward criterion. We develop some variations of the transportation lemma that could serve as novel tools for the regret analysis of RL algorithms. Revisiting existing regret lower bounds allows us to derive alternative bounds, which motivate that the local variance of the bias function of the MDP, i.e., the variance with respect to next-state transition laws, could serve as a notion of problem complexity for regret minimization in RL. Leveraging these tools also allows us to report a novel regret analysis of the KL-UCRL algorithm for ergodic MDPs. The leading term in our regret bound depends on the local variance of the bias function, thus coinciding with observations obtained from our presented lower bounds. Numerical evaluations in some benchmark MDPs indicate that the leading term of the derived bound can provide an order of magnitude improvement over previously known results for this algorithm.

QC 20171215

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Devlin, Agatha. "A study of parallel algorithms for the solution of some combinatorial optimization problems on a distributed array of processors". Thesis, Queen's University Belfast, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.282129.

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Książki na temat "Combinatorial statistics"

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Roux, Brigitte Le. Combinatorial Inference in Geometric Data Analysis. Boca Raton, Florida, USA: Chapman and Hall/CRC, Taylor & Francis Group, 2019.

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Hubert, Lawrence J. Assignment methods in combinatorial data analysis. New York: M. Dekker, 1987.

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1956-, Balakrishnan N., red. Advances in combinatorial methods and applications to probability and statistics. Boston: Birkhäuser, 1997.

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Balakrishnan, N., red. Advances in Combinatorial Methods and Applications to Probability and Statistics. Boston, MA: Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4612-4140-9.

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L, Aarts E. H., i Lenstra J. K, red. Local search in combinatorial optimization. Chichester [England]: Wiley, 1997.

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Bapat, Ravindra B. Combinatorial Matrix Theory and Generalized Inverses of Matrices. India: Springer India, 2013.

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Martin, George E. Counting: The Art of Enumerative Combinatorics. New York, NY: Springer New York, 2001.

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Wright, Tommy. Exact confidence bounds when sampling from small finite universes: An easy reference based on the hypergeometric distribution. Berlin: Springer-Verlag, 1991.

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Barthélemy, Jean-Pierre. Trees and proximity representations. Chichester: Wiley, 1991.

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Ionin, Yuri. Combinatorics of symmetric designs. Cambridge, UK: Cambridge University Press, 2006.

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Części książek na temat "Combinatorial statistics"

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Marshall, Albert W., Ingram Olkin i Barry C. Arnold. "Combinatorial Analysis". W Springer Series in Statistics, 243–67. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-0-387-68276-1_7.

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Lange, Kenneth. "Combinatorial Optimization". W Springer Texts in Statistics, 103–22. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7165-4_5.

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Szpankowski, Wojciech. "Combinatorial optimization through order statistics". W Lecture Notes in Computer Science, 208–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-54945-5_64.

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Wen, Zhenzao, Jiapeng Huang, Linghe Kong, Min-You Wu i Guihai Chen. "Classification Statistics in RFID Systems". W Combinatorial Optimization and Applications, 425–40. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71147-8_29.

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Rubinstein, Reuven Y., i Dirk P. Kroese. "Combinatorial Optimization via Cross-Entropy". W Information Science and Statistics, 129–86. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4757-4321-0_4.

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Hoeffding, Wassily. "A Combinatorial Central Limit Theorem". W Springer Series in Statistics, 237–46. New York, NY: Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-0865-5_12.

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Lengauer, Thomas. "Operations Research and Statistics". W Combinatorial Algorithms for Integrated Circuit Layout, 137–217. Wiesbaden: Vieweg+Teubner Verlag, 1990. http://dx.doi.org/10.1007/978-3-322-92106-2_4.

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Bertsimas, Dimitris, i Yinyu Ye. "Semidefinite Relaxations, Multivariate Normal Distributions, and Order Statistics". W Handbook of Combinatorial Optimization, 1473–91. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4613-0303-9_24.

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Kjos-Hanssen, Bjørn. "Kolmogorov Structure Functions for Automatic Complexity in Computational Statistics". W Combinatorial Optimization and Applications, 652–65. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12691-3_49.

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Fontana, Roberto, i Fabio Rapallo. "Simulations on the Combinatorial Structure of D-Optimal Designs". W Statistics and Simulation, 343–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76035-3_24.

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Streszczenia konferencji na temat "Combinatorial statistics"

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Ishihata, Masakazu, i Takanori Maehara. "Exact Bernoulli Scan Statistics using Binary Decision Diagrams". W Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/795.

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In combinatorial statistics, we are interested in a statistical test of combinatorial correlation, i.e., existence a subset from an underlying combinatorial structure such that the observation is large on the subset. The combinatorial scan statistics has been proposed for such a statistical test; however, it is not commonly used in practice because of its high computational cost. In this study, we restrict our attention to the case that the number of data points is moderately small (e.g., 50), the outcome is binary, and the underlying combinatorial structure is represented by a zero-suppressed binary decision diagram (ZDD), and consider the problem of computing the p-value of the combinatorial scan statistics exactly. First, we prove that this problem is a #P-hard problem. Then, we propose a practical algorithm that solves the problem. Here, the algorithm constructs a binary decision diagram (BDD) for a set of realizations of the random variables by a dynamic programming on the ZDD, and computes the p-value by a dynamic programming on the BDD. We conducted experiments to evaluate the performance of the proposed algorithm using real-world datasets.
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Fejes Tóth, Péter, Ödön Vancsó i Manfred Borovcnik. "Combinatorial Thinking as Key for Introducing Hypothesis Testing—Evaluation of the Planned Secondary-School Reform in Hungary". W Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. International Association for Statistical Education, 2022. http://dx.doi.org/10.52041/iase.icots11.t6f1.

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We developed an educational programme to prepare a curricular reform in Hungary. In the framework of this project, we tested and evaluated a new curriculum design relying on combinatorial and probabilistic knowledge and skills. As opposed to inferential statistics, which is not part of secondary education, combinatorial thinking has a rich tradition in secondary education. The idea was to extend combinatorially introduced probability to a wider meaning of general frequencies by using probability to evaluate the credibility of hypotheses. The materials proved to be interesting, motivating, and understandable. Based on pre- and post-tests, students’ probabilistic knowledge improved significantly. It is worth noting that our approach also intensified their understanding about probability apart from the targeted content of hypothesis testing.
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Kim, Mansuck, i Byung-Jun Yoon. "Efficient combinatorial drug optimization through stochastic search". W 2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS). IEEE, 2011. http://dx.doi.org/10.1109/gensips.2011.6169434.

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Yunlu, Wang, Ye Xueyi i Zhao Zemao. "Steganalysis on echo hiding based on combinatorial high order statistics". W the First International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1734605.1734626.

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Podworny, Susanne, Daniel Frischemeier i Rolf Biehler. "Design, realization and evaluation of a statistics course for preservice teachers for primary school in Germany". W Teaching Statistics in a Data Rich World. International Association for Statistical Education, 2017. http://dx.doi.org/10.52041/srap.17309.

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We designed and developed a statistics course “Data & chance for primary school” that aims at developing content knowledge, pedagogical content knowledge, and technological knowledge of preservice primary school teachers. The course consists of weekly lectures where the content and the technological knowledge components are developed and of a weekly accompanying small- group seminar. The course is designed with statistical reasoning learning environment principles; interface tasks that bridge content knowledge and pedagogical content knowledge play a fundamental role in the course. Three topics are taught: data analysis, combinatorics, and introduction into probability via stochastic simulations. The first results—from online surveys before and after the course (n=189), evaluation of participants’ written homework assignments, and a written test administered after the course—show that statistical thinking of our preservice teachers improves over time and that they show more positive attitudes towards statistics after having attended the course.
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Vogrinec, Monika, i Drago Bokal. "Doseganje višjih kognitivnih ciljev z vključevanjem hackathona v učni proces". W Values, Competencies and Changes in Organizations. University of Maribor Press, 2021. http://dx.doi.org/10.18690/978-961-286-442-2.75.

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With the lack of time and abundance of distractions, to which we are subject to when lecturing and assimilating new knowledge, it is very important to form lecturing processes that allow management of compromises between the learning experiences, goal depth, range of the used concepts, and effective feedback about correct understanding of learned material. In this paper, we present a hackathon concept with outcome directed to specific applicable results. Besides higher efficiency at achieving the goals, the learning process is monitored using a questionnaire, which induces reflection on comprehension of learned concepts. Because of a large amount of autonomous and focused work, the mentee solves the problem with greater quality and uses the questionnaire for recieving feedback as a substitute to grade. In this way, the self-evaluation helps the mentor to indentify the weaknesses of understaning, while simultaneously the examination of self- evaluation with the mentor is the foundation of mentees self- criticism and becomes the tool in formative monitoring regarding assimilation of new knowledge. The hackathon concept is adapted to learning by a reflection of progress in project execution and understanding of the concepts learned along the way at a course on Combinatorial optimization. It is also appropriate for other courses that lecture quantitative methodologies (Mathematican modelling, Operating research, Statistics, subjects of programing and data analytics). The result is a learning process, adapted to the mentee, where the lecturer takes on the role of a mentor. With his in-depth knowledge of the topic, the mentor guides the mentee at searching for solutions of the problem and simultaneously through observation of the mentee adjusts the depth and contents to outset of the mentee and his ability to acquire knowledge.
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Sanjuan, E., M. Parra i I. Castro. "Multimedia tools for the teaching of probability and statistics". W Statistics and the Internet. International Association for Statistical Education, 2003. http://dx.doi.org/10.52041/srap.03312.

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As it is well known, understanding some concepts is not a trivial task for a beginner in the field of the Probability and Statistics. With many students, they are initially greeted with mixed feelings of fear and anger. These feelings inhibit the learning of the probability and statistics. Emphasis has been placed in different directions with respect to the teaching of probability and statistics. Firstly, it focused on reducing the effort needed to perform statistical computations, but gave little insight into the meaning of concepts. Secondly, the emphasis was on meaning, but many of the students in the applied sciences were unprepared for such an approach and ended up knowing neither the theory nor the computational procedures. Our aim is to attempt to make probability and statistics as simple as possible for the student. In this work, we present multimedia tools in order to teach many probability concepts and simulating random experiments. The considered concepts are descriptive statistics, random experiments, sets and events, combinatorics, conditional probability, discrete random variables, continuous random variables, and central limit theorem. The computer is the principal instrument in the realization of these simulations. However, in some cases, the student does not know necessary programming concepts to design the experiments. For this reason, it is very important to supply an appropriate environment to the student for the realization of these experiments. These multimedia tools have been carried out in MATLAB using GUIDE (Graphical User Interface Development). The GUI Design Enviroment tools allow Handle Graphics objects to be manipulated interactively. These GUI's allow creating a teaching interactive environment. The student can select different values of the parameters in an easy way using command buttons, scroll bars and list and edit boxes without programming. The results are displayed using graphics, animations and related numerical values. The GUI's are completed with text. This text is a summary of the underlying mathematical theory related to the GUI'S. Matlab Web Server will provide an access via web to these tools. It implies an easy export of this tool to different operating systems and the virtual teaching. This tool is expected to be applied in the next academic course in the Department of Mathematics of the University of Extremadura (Spain).
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Wang, Dingwei. "Theoretical and statistic analysis on necessary bidder numbers for combinatorial auctions". W 2012 24th Chinese Control and Decision Conference (CCDC). IEEE, 2012. http://dx.doi.org/10.1109/ccdc.2012.6244330.

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Fernández, Nicolás, Jaime García-García, Elizabeth Arredondo i Isaac Imilpán. "Knowledge of Binomial Distribution in Pre-service Mathematics Teachers". W Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. International Association for Statistical Education, 2022. http://dx.doi.org/10.52041/iase.icots11.t8b2.

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The binomial distribution is one of the most important discrete distributions in probability and statistics; however, research identifies weaknesses in teachers’ and students’ application of binomial distributions for solving tasks beyond the direct use of the formula. Based on historical epistemological study and notions from the onto-semiotic approach to mathematical knowledge and instruction, we designed and administered a questionnaire to secondary school mathematics teachers in training. In our results, we identify and describe a lack of articulation among historical epistemological elements of the binomial distribution. Teachers can correctly use concepts such as combinatorics, probability, and the binomial distribution formula to model and identify binomial phenomena but cannot answer questions about a random variable or expected value. They show a lack of consideration of alternative representations.
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Huang, Denggao, Hui Xie, Qiang Sun, Hongjie Ma i Tielong Shen. "A statistical evaluation model for driver-bus-route combinatorial optimization". W 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE). IEEE, 2015. http://dx.doi.org/10.1109/sice.2015.7285419.

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Raporty organizacyjne na temat "Combinatorial statistics"

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Mossel, Elchanan. Combinatorial Statistics on Trees and Networks. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 2010. http://dx.doi.org/10.21236/ada531376.

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Srivastava, J. Multivariate Problems of Statistics, Combinatorics, Reliability, and Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, październik 1992. http://dx.doi.org/10.21236/ada265213.

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Srivastava, J. N. Bose Memorial Conference on Statistical Design and Related Combinatorics. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 1995. http://dx.doi.org/10.21236/ada299907.

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Srivastava, J. N. Bose Memorial Conference on Statistical Design and Related Combinatorics. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 1995. http://dx.doi.org/10.21236/ada300029.

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