Relevant bibliographies by topics / Mathematical statistics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Mathematical statistics'

Author: Grafiati
Published: 4 June 2021
Last updated: 29 July 2024

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Journal articles on the topic "Mathematical statistics"

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McCullough, B. D. "Mathematical Statistics With Mathematica." Journal of the American Statistical Association 97, no. 460 (December 2002): 1202–3. http://dx.doi.org/10.1198/jasa.2002.s230.

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Attwood, G. B., John E. Freund, and Ronald E. Walpole. "Mathematical Statistics." Mathematical Gazette 72, no. 459 (March 1988): 76. http://dx.doi.org/10.2307/3618025.

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Lindley, D. V., A. A. Borovkov, and A. Moullagaliev. "Mathematical Statistics." Mathematical Gazette 83, no. 497 (July 1999): 374. http://dx.doi.org/10.2307/3619119.

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Strawderman, William E., and Jun Shao. "Mathematical Statistics." Journal of the American Statistical Association 95, no. 449 (March 2000): 329. http://dx.doi.org/10.2307/2669561.

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Jammalamadaka, Sreenivasa Rao, and A. A. Borovkov. "Mathematical Statistics." Journal of the American Statistical Association 95, no. 449 (March 2000): 330. http://dx.doi.org/10.2307/2669562.

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Pillers Dobler, Carolyn. "Mathematical Statistics." American Statistician 56, no. 4 (November 2002): 332. http://dx.doi.org/10.1198/tas.2002.s204.

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Geyer, C. "Mathematical Statistics." Journal of the American Statistical Association 96, no. 454 (June 2001): 779. http://dx.doi.org/10.1198/jasa.2001.s397.

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Massam, Hélène. "Mathematical Statistics." Journal of Statistical Planning and Inference 92, no. 1-2 (January 2001): 305–6. http://dx.doi.org/10.1016/s0378-3758(00)00154-3.

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KRASNOZHON, O. B., and V. V. MATSIUK. "КОМП’ЮТЕРНО-ОРІЄНТОВАНІ ЕЛЕМЕНТИ НАВЧАННЯ МАТЕМАТИЧНИХ ДИСЦИПЛІН МАЙБУТНІХ УЧИТЕЛІВ МАТЕМАТИКИ." Scientific papers of Berdiansk State Pedagogical University Series Pedagogical sciences 1, no. 2 (October 4, 2021): 255–62. http://dx.doi.org/10.31494/2412-9208-2021-1-2-255-262.

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The article is devoted to the issues of constructing effective computer-oriented components of the methodological system of teaching the disciplines «Linear Algebra» and «Probability Theory with Elements of Mathematical Statistics» provided for in the educational and professional program «Secondary Education (Mathematics)» of the first level of higher education in the specialty 014 Secondary Education (Mathematics). The article analyzes the methodological aspects of the effective organization of computations when finding the angle between a given vector and a nonzero subspace of Euclidean space, as well as using the least squares method for processing experimental data. The theoretical and practical information known to students-mathematicians from the corresponding sections of these academic disciplines is briefly presented. Analyzed educational, methodological and scientific literature used in teaching linear algebra and probability theory with elements of mathematical statistics; the expediency of using computer-oriented elements of teaching mathematical disciplines of future mathematics teachers has been substantiated. The authors proposed the use of computer-oriented learning elements in the processing of the content of disciplines and the development of test tasks of different levels of complexity in linear algebra and probability theory with elements of mathematical statistics in order to objectively assess the level of students' knowledge and timely correct individual educational trajectories. The article provides examples of the application of computer-oriented elements of teaching linear algebra and probability theory with elements of mathematical statistics, and also analyzes the methodological features of the organization of calculations in the software mathematical environment Mathcad. The methodological and practical materials presented in the article can be useful for students to organize and activate independent scientific and pedagogical activities, teachers of secondary educational institutions, heads of optional and circle work of students, teachers of linear algebra and probability theory courses with elements of mathematical statistics of pedagogical higher educational institutions. Key words: methods of teaching mathematics, computer-oriented elements of teaching mathematics, linear algebra, probability theory, mathematical statistics, Euclidean space, non-zero subspace of Euclidean space, least squares method.
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Madsen, Richard, Edward J. Dudewicz, and Satya N. Mishra. "Modern Mathematical Statistics." Journal of the American Statistical Association 84, no. 405 (March 1989): 335. http://dx.doi.org/10.2307/2289889.

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Dissertations / Theses on the topic "Mathematical statistics"

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Carlqvist, Håkan. "Multiscale analysis of multi-channel signals." Doctoral thesis, KTH, Matematik (Avd.), 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-230.

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I: Amplitude and phase relationship between alpha and beta oscillations in the human EEG We have studied the relation between two oscillatory patterns within EEG signals (oscillations with main frequency 10 Hz and 20 Hz), with wavelet-based methods. For better comparison, a variant of the continuous wavelet transform, was derived. As a conclusion, the two patterns were closely related and 70-90 % of the activity in the 20 Hz pattern could be seen as a resonance phenomenon of the 10 Hz activity. II: A local discriminant basis algorithm using wavelet packets for discrimination between classes of multidimensional signals We have improved and extended the local discriminant basis algorithm for application on multidimensional signals appearing from multichannels. The improvements includes principal-component analysis and crossvalidation- leave-one out. The method is furthermore applied on two classes of EEG signals, one group of control subjects and one group of subjects with type I diabetes. There was a clear discrimination between the two groups. The discrimination follows known differences in the EEG between the two groups of subjects. III: Improved classification of multidimensional signals using orthogonality properties of a time-frequency library We further improve and refine the method in paper2 and apply it on 4 classes of EEG signals from subjects differing in age and/or sex, which are known factors of EEG alterations. As a method for deciding the best basis we derive an orthogonalbasis- pursuit-like algorithm which works statistically better (Tukey's test for simultaneous confidence intervals) than the basis selection method in the original local discriminant basis algorithm. Other methods included were Fisher's class separability, partial-least-squares and cross-validation-leave-one-subject out. The two groups of younger subjects were almost fully discriminated between each other and to the other groups, while the older subjects were harder to discriminate.
QC 20101001
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Tovo, Anna. "Mathematical modelling and statistics of biodiversity." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3421944.

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Life on Earth is characterised by an amazing variety of living forms which are in continuous evolution to better adapt to the surrounding environment and highly connected one to the other. A deep investigation of different living systems has recently been favoured by the huge quantity of data nowadays available. The present thesis is the final result of a journey through complex patterns in theoretical ecology. We study both models and issues in data analysis as well as the connections between them within a mathematical framework. In particular, we explore the different aspects of the biodiversity of an ecosystem, referring with this term to the variety of its species. Our interest is to investigate how these species interact with each other and with the surrounding environment and how these connections can structure recurrent macro-ecological patterns. Indeed, despite their diversity and complexity, it is straightforward that ecological systems share similar behaviours. This fact suggests that such systems are driven by a common mechanism, which is insensitive to the details of the systems on which it acts. A theoretical understanding is therefore possible through the development of mathematical models rich enough to reproduce the investigated patterns, but containing only the essential ingredients able to originate them. In the first part of the present thesis, we explore the fundamentals of spatial point process theory, a powerful mathematical tool to model data in the form of sets of spatial locations of points. In particular, since our datasets usually consist of information on trees belonging to different species, we focus on the so-called superposed process and its first and second-order statistics. We then study an algorithm to infer the intensity function of a point process which is capable to reduce sampling fluctuations and to capture relevant spatial characteristics of a spatial pattern, as space anisotropy and clustering. Finally, we explore in details the notions of ecological diversity and similarity and some of the most popular indexes used to measure them. In particular, we study how to insert them in the context of point processes’ theory. Our aim is at finding an analytical relation for the decay of similarity between two regions of a landscape as a function of the distance between them, by extending the classic notion of Sørensen’s index to incorporate spatial information. In the second part of the thesis, we tackle the problem of inferring the total bio- diversity of an ecosystem when only scattered samples are observed. In particular, we propose a novel upscaling method which, by exploiting the scaling invariance property of the negative binomial distribution, generates accurate and robust pre- dictions. We test it on both computer-generated and real forests and we show that it outperforms other methods previously proposed in literature.
La vita sulla Terra è caratterizzata da una straordinaria varietà di forme viventi in continua evoluzione per meglio adattarsi all’ambiente circostante e strettamente connesse le une alle altre. Oggigiorno, grazie all’enorme quantità di dati a disposizione, è possibile investigare a fondo su diversi sistemi viventi. La presente tesi è il risultato di un percorso attraverso i complessi pattern della teoria ecologica. In essa trattiamo sia modelli teorici sia problematiche legate all’analisi dei dati, come anche le connessioni tra loro, tutto all’interno di un contesto matematico. Centro d’interesse sono i diversi aspetti della biodiversità di un ecosistema, termine con il quale indichiamo la varietà delle sue specie. In particolare, vogliamo investigare il modo in cui le diverse specie interagiscono le une con le altre e come, da queste connessioni, possano originarsi dei pattern macro-ecologici ricorrenti. Infatti, nonostante la loro apparente diversità e complessità, è oggi evidente che i sistemi ecologici mostrano comportamenti simili. Questo fatto suggerisce che tali sistemi evolvono secondo un meccanismo comune, insensibile ai dettagli del sistema su cui agisce. Di conseguenza, si apre la strada allo sviluppo di modelli teorici che siano abbastanza complessi da riuscire a spiegare tali fenomeni, ma che al contempo non contengano più dettagli di quelli necessari a riprodurli. La prima parte della tesi è dedicata all’esplorazione dei fondamenti della teoria dei processi di punto, uno strumento matematico molto utile quando si va ad investigare dataset contenenti posizioni di punti nello spazio. In particolare, essendo i nostri database relativi a coordinate di alberi appartenenti a specie diverse, ci concentreremo sul cosiddetto processo sovrapposto e sulle sue statistiche di primo e secondo ordine. Poi studieremo un algoritmo che permette di ottenere informazioni sull’intensità di un processo di punto, capace al contempo di ridurre le fluttuazioni di campionamento e di rivelare caratteristiche importanti di un pattern spaziale, come l’anisotropia ed il clustering. Infine, esploreremo in dettaglio le nozioni di diversità e similarità e i vari indici proposti in letteratura per misurarle. In particolare, studieremo come inserire queste nozioni nel contesto dei processi di punto. L’obiettivo è quello di trovare una relazione analitica per il decadimento di similarità tra due regioni in funzione della distanza tra esse estendendo la nozione classica dell’indice di Sørensen in modo da incorporare informazioni spaziali. Nella seconda parte della tesi, affronteremo il problema di inferire la biodiversità totale di un ecosistema avendo a disposizione solo alcuni suoi campioni. In particolare, proporremo un nuovo metodo che, sfruttando la proprietà di invarianza di scala della distribuzione binomiale negativa, permette di avere stime accurate e robuste. Testandolo sia su foreste artificiali che reali, mostreremo che il metodo è più affidabile rispetto ad altri proposti in letteratura.
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Parks, Sarah Louise. "Mathematical models and statistics for evolutionary inference." Thesis, University of Cambridge, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708749.

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Hua, Hairui. "Survival modelling in mathematical and medical statistics." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/5808/.

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An essential aspect of survival analysis is the estimation and prediction of survival probabilities for individuals. For this purpose, mathematical modelling of the hazard rate function is a fundamental issue. This thesis focuses on the novel estimation and application of hazard rate functions in mathematical and medical research. In mathematical research we focus on the development of a semiparametric kernel-based estimate of hazard rate function and a L\(_1\) error optimal kernel hazard rate estimate. In medical research we concentrate on the development and validation of survival models using individual participant data from multiple studies. We also consider how to fit survival models that predict individual response to treatment effectiveness, given IPD from multiple trials.
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Thulin, Måns. "On two classic problems in statistics." Licentiate thesis, Uppsala universitet, Matematisk statistik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-171962.

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Groth, Randall E. Langrall Cynthia Willey Mooney Edward S. "Development of a high school statistical thinking framework." Normal, Ill. Illinois State University, 2003. http://wwwlib.umi.com/cr/ilstu/fullcit?p3087867.

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Thesis (Ph. D.)--Illinois State University, 2003.
Title from title page screen, viewed November 10, 2005. Dissertation Committee: Cynthia W. Langrall, Edward S. Mooney (co-chair), Beverly J. Hartter, Sharon S. McCrone. Includes bibliographical references (leaves 199-212) and abstract. Also available in print.
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Zhang, You You. "Brownian excursions in mathematical finance." Thesis, London School of Economics and Political Science (University of London), 2014. http://etheses.lse.ac.uk/3058/.

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The Brownian excursion is defined as a standard Brownian motion conditioned on starting and ending at zero and staying positive in between. The first part of the thesis deals with functionals of the Brownian excursion, including first hitting time, last passage time, maximum and the time it is achieved. Our original contribution to knowledge is the derivation of the joint probability of the maximum and the time it is achieved. We include a financial application of our probabilistic results on Parisian default risk of zero-coupon bonds. In the second part of the thesis the Parisian, occupation and local time of a drifted Brownian motion is considered, using a two-state semi-Markov process. New versions of Parisian options are introduced based on the probabilistic results and explicit formulae for their prices are presented in form of Laplace transforms. The main focus in the last part of the thesis is on the joint probability of Parisian and hitting time of Brownian motion. The difficulty here lies in distinguishing between different scenarios of the sample path. Results are achieved by the use of infinitesimal generators on perturbed Brownian motion and applied to innovative equity exotics as generalizations of the Barrier and Parisian option with the advantage of being highly adaptable to investors’ beliefs in the market.
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Rezaei, Sadegh. "The mathematical analysis of crossover designs." Title page, contents and summary only, 1997. http://web4.library.adelaide.edu.au/theses/09PH/09phr4668.pdf.

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Paine, Andrew Steven. "The mathematical modelling of rock blasting." Thesis, University of Southampton, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315504.

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Fletcher, Matthew. "Mathematical topics in coding and cryptology." Thesis, University of Bath, 1992. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.317570.

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Books on the topic "Mathematical statistics"

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Rose, Colin, and Murray D. Smith. Mathematical Statistics with Mathematica®. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4612-2072-5.

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Rasch, Dieter, and Dieter Schott. Mathematical Statistics. Chichester, UK: John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119385295.

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Rossi, Richard J. Mathematical Statistics. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781118771075.

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Shao, Jun. Mathematical Statistics. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/b97553.

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Pfanzagl, Johann. Mathematical Statistics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-642-31084-3.

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Arnold, Steven F. Mathematical statistics. London: Prentice-Hall International, 1990.

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E, Walpole Ronald, ed. Mathematical statistics. 4th ed. Englewood Cliffs, N.J: Prentice-Hall, 1987.

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E, Freund John. Mathematical statistics. 5th ed. Englewood Cliffs, N.J: Prentice Hall, 1992.

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E, Freund John. Mathematical statistics. 4th ed. London: Prentice-Hall International, 1987.

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Shao, Jun. Mathematical statistics. 2nd ed. New York: Springer, 2010.

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Book chapters on the topic "Mathematical statistics"

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Cipra, Tomáš. "Mathematical Statistics." In Survey of Applicable Mathematics, 1451–81. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-015-8308-4_34.

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Abraham, Douglas A. "Mathematical Statistics." In Modern Acoustics and Signal Processing, 251–305. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-92983-5_5.

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Csáki, Endre. "Mathematical Statistics." In Bolyai Society Mathematical Studies, 491–521. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-30721-1_16.

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Rose, Colin, and Murray D. Smith. "mathStatica: Mathematical Statistics with Mathematica." In Compstat, 437–42. Heidelberg: Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-642-57489-4_66.

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Flury, Bernhard, and Hans Riedwyl. "Mathematical appendix." In Multivariate Statistics, 276–87. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1217-5_13.

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Birolini, Alessandro. "Basic Mathematical Statistics." In Reliability Engineering, 435–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03792-8_16.

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Maccone, Claudio. "Societal statistics by the statistical Drake equation." In Mathematical SETI, 239–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27437-4_9.

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Saunders, Sam C. "Mathematical Appendix." In Springer Series in Statistics, 289–98. New York, NY: Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-48538-6_16.

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Pfeiffer, Paul E. "Mathematical Expectation." In Springer Texts in Statistics, 275–85. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4615-7676-1_15.

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Thulin, Måns. "Mathematical appendix." In Modern Statistics with R, 449–56. 2nd ed. Boca Raton: Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003401339-14.

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Conference papers on the topic "Mathematical statistics"

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Kuzmak, Sylvia. "Mapping knowledge for probability and statistics application: mathematical and non-mathematical." In Promoting Understanding of Statistics about Society. International Association for Statistical Education, 2016. http://dx.doi.org/10.52041/srap.16105.

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A mapping (a cognitive analysis) of knowledge used in the effective application of probability and statistics in real world situations is presented, identifying both mathematical and non- mathematical knowledge involved. The fundamental role of domain-related knowledge and expertise is emphasized, with illustrations provided using applications involving social data. Use of the knowledge mapping to support improvement of educational practice is proposed, including its use as a basis to evaluate the completeness of current curriculum and instruction in applied probability and statistics, to guide the design of more complete and effective curriculum and instruction, to guide curriculum design across university departments, and to evaluate curriculum and instruction at all grade levels to ensure misapplication of probability and statistics is not taught.
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del Pino, Guido, and Ana Araneda. "Connecting mathematical and statistical teaching: the role of statistical variables." In Advances in Statistics Education: Developments, Experiences, and Assessments. International Association for Statistical Education, 2015. http://dx.doi.org/10.52041/srap.15117.

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Teaching statistics is unappealing to most high school teachers, in part due to their deficient university training in this field and to the fact that people with a strong mathematical preparation tend to look down on areas that use only elementary mathematics. To lessen this problem this paper establishes some connections between descriptive statistics, probability, and mathematics, comparing statistical variables, random variables, and functions. Several arguments are given to justify that in statistical applications, it is not the function representing the variable that matters, but the key element is the induced frequency distribution, which is important for the teaching probability theory. Some pedagogical ideas are given for teaching continuous variables, a topic that poses subtle mathematical issues, like the meaning of a real number, of continuous functions, and of infinite domains, and that the exact value of a continuous variable is not observable.
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Watanabe, S., M. Fukushima, Yu V. Prohorov, and A. N. Shiryaev. "PROBABILITY THEORY AND MATHEMATICAL STATISTICS." In Seventh Japan–Russia Symposium. WORLD SCIENTIFIC, 1996. http://dx.doi.org/10.1142/9789814532181.

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Gattuso, Linda. "Mathematics in a statistical context?" In Joint ICMI/IASE Study: Teaching Statistics in School Mathematics. International Association for Statistical Education, 2008. http://dx.doi.org/10.52041/srap.08701.

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Statistics is often taught as part of the mathematical curriculum in schools by mathematics teachers who often do not feel prepared to include it in their practice. They feel that they are stealing time that would be better used if dedicated to mathematics. We believe, however, that it is possible to develop a collaboration between the teaching of mathematics and the teaching of statistics. Using statistics as a realistic context to work on certain mathematical concepts can provide significant motivation for students. To accomplish this, it is essential to highlight the mathematical concepts underlying statistical concepts in order to link them in creating classroom activities that are also useful for teacher training. In this paper, we will try to illustrate this idea starting with examples gathered in school mathematics and in basic statistics.
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Jones, Peter, Kay Lipson, and Brian Phillips. "A role for computer intensive methods in introducing statistical inference." In Proceedings of the First Scientific Meeting of the IASE. International Association for Statistical Education, 1993. http://dx.doi.org/10.52041/srap.93311.

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Introductory statistics courses have become increasingly prevalent in a wide variety of undergraduate and graduate programs over the past few years. This has resulted in the study of inferential statistics becoming the norm rather than exception. Whilst statistics was once a course chosen by the more mathematically able student, many current students of statistics have little mathematical aptitude or expertise (Tanis, 1992 for example). As a result, many introductory statistic courses have moved away from including much of the statistical theory that underpins inference to become basically technique oriented "recipe book" courses. the internet danger of producing students capable of performing various complex statistical tests without really knowing what they are doing is obvious, particularly if the house includes the use of a sophisticated statistical computer package.
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Ulrychová, Eva, and Diana Bílková. "Students’ knowledge of mathematical definitions." In International Days of Statistics and Economics 2019. Libuše Macáková, MELANDRIUM, 2019. http://dx.doi.org/10.18267/pr.2019.los.186.156.

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Ottaviani, Maria Gabriella, and Silio Rigatti Luchini. "“Data and Predictions” Emerging as One of the Basic Themes in the Mathematical Curriculum of the First Cycle School Level in Italy." In Curricular Development in Statistics Education. International Association for Statistical Education, 2004. http://dx.doi.org/10.52041/srap.04501.

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In the reform of the Italian school system, a new pedagogical point of view has shifted attention away from content and skills and toward competencies. Also contributing to the proposal of a new mathematical curriculum is a new way of looking at mathematics that takes globalised societal needs into consideration. This paper describes the role of the Italian Statistical Society (SIS) in proposing knowledge and skills of the “Data and predictions” nucleus, which has emerged as one of the basic themes in the new mathematics curriculum. We present the guidelines which have been implemented to enhance the visibility of statistics and probability in the mathematical curriculum, taking into account the results of some recent research on statistics education carried out in Italy.
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Chopperfield, James, Siu-Ming Tam, and Paul Schubert. "Building expertise in mathematical statistics within the Australian bureau of statistics through partnerships with academics." In Statistics education for Progress: Youth and Official Statistics. International Association for Statistical Education, 2013. http://dx.doi.org/10.52041/srap.131001.

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Australian Bureau of Statistics recognises the critical importance that its statistical products and services are underpinned by defensive statistical methodology. To this end, the Australian Bureau of Statistics has developed strong partnerships with academics and universities in order to assist with the recruitment of graduates and their development into research leaders in mathematical statisticians. This paper describes the details of the partnerships since 2004 and some of the important benefits.
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Bogdanov, Yu I. "Quantum mechanical view of mathematical statistics." In SPIE Proceedings, edited by Yuri I. Ozhigov. SPIE, 2006. http://dx.doi.org/10.1117/12.683116.

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Yozza, Hazmira, Yudiantri Asdi, and Izzati Rahmi. "Blended Learning in Mathematical Statistics I." In Proceedings of the 2nd International Conference on Educational Development and Quality Assurance, ICED-QA 2019, 11 September 2019, Padang, Indonesia. EAI, 2021. http://dx.doi.org/10.4108/eai.11-9-2019.2298482.

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Reports on the topic "Mathematical statistics"

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Liskina, E. YU. Electronic textbook «Mathematical statistics» for students of the fields of study 01.03.01 Mathematics, 01.03.05 Statistics. Ryazan State University named for S.Yesenin, March 2024. http://dx.doi.org/10.12731/ofernio.2024.25301.

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Ilyin, M. E. The distance learning course «Theory of probability, mathematical statistics and random functions». OFERNIO, December 2018. http://dx.doi.org/10.12731/ofernio.2018.23529.

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Wang, Zhi, Mark Gehlhar, and Shunli Yao. Reconciling Trade Statistics from China, Hong Kong and Their Major Trading Partners--A Mathematical Programming Approach. GTAP Technical Paper, September 2007. http://dx.doi.org/10.21642/gtap.tp27.

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This paper develops a mathematical programming model to simultaneously estimate re-export markups and reconcile bilateral trade statistics between China, Hong Kong, and their trading partners. The model is applied to sector level trade flows to resolve discrepant reporting in an efficient manner. Adjustments in trade flows are based upon statistical reporters’ reliability information. The program is implemented in GAMS and retains many desirable theoretical and empirical properties. Estimates are used for generating trade flows and markups for Hong Kong’s re-exports used in the forthcoming version 7 GTAP database. The model’s flexibility has potential for expanded use in other regions where re-exports and associated markup cause discrepant trade flows.
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Lovianova, Iryna V., Dmytro Ye Bobyliev, and Aleksandr D. Uchitel. Cloud calculations within the optional course Optimization Problems for 10th-11th graders. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3267.

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The article deals with the problem of introducing cloud calculations into 10th-11th graders’ training to solve optimization problems in the context of the STEM-education concept. After analyzing existing programmes of optional courses on optimization problems, the programme of the optional course Optimization Problems has been developed and substantiated implying solution of problems by the cloud environment CoCalc. It is a routine calculating operation and not a mathematical model that is accentuated in the programme. It allows considering more problems which are close to reality without adapting the material while training 10th-11th graders. Besides, the mathematical apparatus of the course which is partially known to students as the knowledge acquired from such mathematics sections as the theory of probability, mathematical statistics, mathematical analysis and linear algebra is enough to master the suggested course. The developed course deals with a whole class of problems of conventional optimization which vary greatly. They can be associated with designing devices and technological processes, distributing limited resources and planning business functioning as well as with everyday problems of people. Devices, processes and situations to which a model of optimization problem is applied are called optimization problems. Optimization methods enable optimal solutions for mathematical models. The developed course is noted for building mathematical models and defining a method to be applied to finding an efficient solution.
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Olefirenko, Nadiia V., Ilona I. Kostikova, Nataliia O. Ponomarova, Kateryna O. Lebedieva, Vira M. Andriievska, and Andrey V. Pikilnyak. Training elementary school teachers-to-be at Computer Science lessons to evaluate e-tools. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3890.

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The study purpose is to develop methodological support for students’ training for evaluation e-tools for young learners and to check its effectiveness experimentally. The module “Expert evaluation of the quality of e-tools for young learners” is offered for teachers-to-be. The determination of the weighting factor of each criterion by expert evaluations was organized. Educational principles, correlation e-tool content with the curriculum, interactivity, multimedia, assistance system, ergonomic requirements are mentioned. On the basis of the criterion rank, the significance of each criterion was calculated. The indicators to determine the level of preliminary expert evaluations of e-tools are proposed. The results are calculated with nonparametric methods of mathematical statistics, in particular, Pearson’s criterion χ2. The conclusion is the expert evaluation has different activity stages, gradually becoming a common phenomenon. Training teachers-to-be for e-tool expert evaluation at Computer Science, Mathematics, English is a complex process.
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Peters, Vanessa, Deblina Pakhira, Latia White, Rita Fennelly-Atkinson, and Barbara Means. Designing Gateway Statistics and Chemistry Courses for Today’s Students: Case Studies of Postsecondary Course Innovations. Digital Promise, August 2022. http://dx.doi.org/10.51388/20.500.12265/162.

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Scholars of teaching and learning examine the impacts of pedagogical decisions on students’ learning and course success. In this report, we describes findings from case studies of eight innovative postsecondary introductory statistics and general chemistry courses that have evidence of improving student completion rates for minoritized and low-income students. The goal of the case studies was to identify the course design elements and pedagogical practices that were implemented by faculty. To identify courses, Digital Promise sought nominations from experts in statistics and chemistry education and reviewed National Science Foundation project abstracts in the Improving Undergraduate STEM Education (IUSE) program. The case studies courses were drawn from 2- and 4-year colleges and were implemented at the level of individual instructors or were part of a department or college-wide intervention. Among the selected courses, both introductory statistics (n = 5) and general chemistry (n = 3) involved changes to the curriculum and pedagogy. Curricular changes involved a shift away from teaching formal mathematical and chemical equations towards teaching that emphasizes conceptual understanding and critical thinking. Pedagogical changes included the implementation of peer-based active learning, formative practice, and supports for students’ metacognitive and self-regulation practices.
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Meza, Juan, Scott Campbell, and David Bailey. Mathematical and Statistical Opportunities in Cyber Security. Office of Scientific and Technical Information (OSTI), March 2009. http://dx.doi.org/10.2172/950976.

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Clausen, Jay, Christopher Felt, Michael Musty, Vuong Truong, Susan Frankenstein, Anna Wagner, Rosa Affleck, Steven Peckham, and Christopher Williams. Modernizing environmental signature physics for target detection—Phase 3. Engineer Research and Development Center (U.S.), March 2022. http://dx.doi.org/10.21079/11681/43442.

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The present effort (Phase 3) builds on our previously published prior efforts (Phases 1 and 2), which examined methods of determining the probability of detection and false alarm rates using thermal infrared for buried object detection. Environmental phenomenological effects are often represented in weather forecasts in a relatively coarse, hourly resolution, which introduces concerns such as exclusion or misrepresentation of ephemera or lags in timing when using this data as an input for the Army’s Tactical Assault Kit software system. Additionally, the direct application of observed temperature data with weather model data may not be the best approach because metadata associated with the observations are not included. As a result, there is a need to explore mathematical methods such as Bayesian statistics to incorporate observations into models. To better address this concern, the initial analysis in Phase 2 data is expanded in this report to include (1) multivariate analyses for detecting objects in soil, (2) a moving box analysis of object visibility with alternative methods for converting FLIR radiance values to thermal temperature values, (3) a calibrated thermal model of soil temperature using thermal IR imagery, and (4) a simple classifier method for automating buried object detection.
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Hlushak, Oksana M., Svetlana O. Semenyaka, Volodymyr V. Proshkin, Stanislav V. Sapozhnykov, and Oksana S. Lytvyn. The usage of digital technologies in the university training of future bachelors (having been based on the data of mathematical subjects). [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3860.

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This article demonstrates that mathematics in the system of higher education has outgrown the status of the general education subject and should become an integral part of the professional training of future bachelors, including economists, on the basis of intersubject connection with special subjects. Such aspects as the importance of improving the scientific and methodological support of mathematical training of students by means of digital technologies are revealed. It is specified that in order to implement the task of qualified training of students learning econometrics and economic and mathematical modeling, it is necessary to use digital technologies in two directions: for the organization of electronic educational space and in the process of solving applied problems at the junction of the branches of economics and mathematics. The advantages of using e-learning courses in the educational process are presented (such as providing individualization of the educational process in accordance with the needs, characteristics and capabilities of students; improving the quality and efficiency of the educational process; ensuring systematic monitoring of the educational quality). The unified structures of “Econometrics”, “Economic and mathematical modeling” based on the Moodle platform are the following ones. The article presents the results of the pedagogical experiment on the attitude of students to the use of e-learning course (ELC) in the educational process of Borys Grinchenko Kyiv University and Alfred Nobel University (Dnipro city). We found that the following metrics need improvement: availability of time-appropriate mathematical materials; individual approach in training; students’ self-expression and the development of their creativity in the e-learning process. The following opportunities are brought to light the possibilities of digital technologies for the construction and research of econometric models (based on the problem of dependence of the level of the Ukrainian population employment). Various stages of building and testing of the econometric model are characterized: identification of variables, specification of the model, parameterization and verification of the statistical significance of the obtained results.
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Kotecha, Meena. Teaching mathematics and statistics: Promoting students' engagement and interaction. Bristol, UK: The Economics Network, January 2012. http://dx.doi.org/10.53593/n2054a.

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