Добірка наукової літератури з теми "Statistics"

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Статті в журналах з теми "Statistics":

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Durbin, J. "Statistics and Statistical Science." Journal of the Royal Statistical Society. Series A (General) 150, no. 3 (1987): 177. http://dx.doi.org/10.2307/2981472.

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Fernholz, Robert, and Cary Maguire. "The Statistics of Statistical Arbitrage." Financial Analysts Journal 63, no. 5 (September 2007): 46–52. http://dx.doi.org/10.2469/faj.v63.n5.4839.

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Fernholz, Robert, and Cary Maguire. "The Statistics of Statistical Arbitrage." CFA Digest 38, no. 1 (February 2008): 83–84. http://dx.doi.org/10.2469/dig.v38.n1.34.

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Pant, N., A. Rotti, and T. Souradeep. "Statistics of statistical anisotropy measures." Journal of Physics: Conference Series 484 (March 5, 2014): 012046. http://dx.doi.org/10.1088/1742-6596/484/1/012046.

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Nelder, John A. "From Statistics to Statistical Science." Journal of the Royal Statistical Society: Series D (The Statistician) 48, no. 2 (July 1999): 257–69. http://dx.doi.org/10.1111/1467-9884.00187.

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BEYTH-MAROM, RUTH, FIONA FIDLER, and GEOFF CUMMING. "STATISTICAL COGNITION: TOWARDS EVIDENCE-BASED PRACTICE IN STATISTICS AND STATISTICS EDUCATION." STATISTICS EDUCATION RESEARCH JOURNAL 7, no. 2 (November 29, 2008): 20–39. http://dx.doi.org/10.52041/serj.v7i2.468.

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Practitioners and teachers should be able to justify their chosen techniques by taking into account research results: This is evidence-based practice (EBP). We argue that, specifically, statistical practice and statistics education should be guided by evidence, and we propose statistical cognition (SC) as an integration of theory, research, and application to support EBP. SC is an interdisciplinary research field, and a way of thinking. We identify three facets of SC—normative, descriptive, and prescriptive— and discuss their mutual influences. Unfortunately, the three components are studied by somewhat separate groups of scholars, who publish in different journals. These separations impede the implementation of EBP. SC, however, integrates the facets and provides a basis for EBP in statistical practice and education. First published November 2008 at Statistics Education Research Journal: Archives
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BEYTH-MAROM, RUTH, FIONA FIDLER, and GEOFF CUMMING. "STATISTICAL COGNITION: TOWARDS EVIDENCE-BASED PRACTICE IN STATISTICS AND STATISTICS EDUCATION." STATISTICS EDUCATION RESEARCH JOURNAL 7, no. 2 (November 29, 2008): 20–39. http://dx.doi.org/10.52041/serj.v7i2.468.

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Practitioners and teachers should be able to justify their chosen techniques by taking into account research results: This is evidence-based practice (EBP). We argue that, specifically, statistical practice and statistics education should be guided by evidence, and we propose statistical cognition (SC) as an integration of theory, research, and application to support EBP. SC is an interdisciplinary research field, and a way of thinking. We identify three facets of SC—normative, descriptive, and prescriptive— and discuss their mutual influences. Unfortunately, the three components are studied by somewhat separate groups of scholars, who publish in different journals. These separations impede the implementation of EBP. SC, however, integrates the facets and provides a basis for EBP in statistical practice and education. First published November 2008 at Statistics Education Research Journal: Archives
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SAIDI, SITI SHAHIRAH, and NYET MOI SIEW. "ASSESSING SECONDARY SCHOOL STUDENTS’ STATISTICAL REASONING, ATTITUDE TOWARDS STATISTICS, AND STATISTICS ANXIETY." STATISTICS EDUCATION RESEARCH JOURNAL 21, no. 1 (February 28, 2022): 6. http://dx.doi.org/10.52041/serj.v21i1.67.

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Assessment on statistical reasoning is an area of academic interest in statistics education research in tandem with attitudes and anxiety towards statistics, since many studies report students are likely to encounter problems with statistics due to these two non-cognitive factors. In this study, 320 Tenth Grade science stream students from Sabah, Malaysia were tested using the Statistical Reasoning Test Survey (SRTS), the Survey of Attitudes towards Statistics (SATS), and the Statistical Anxiety Scale (SAS), which assessed their statistical reasoning, attitude, and anxiety, respectively. Generally, the findings revealed the students held i) a quantitative level in statistical reasoning, ii) a positive attitude towards statistics, and iii) a moderate level of statistics anxiety. A positive relationship between attitudes towards statistics and statistical reasoning, and a negative relationship between statistics anxiety and statistical reasoning were also observed. The Value, Interest, and Interpretation Anxiety components were predictor variables for statistical reasoning.
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Klaus, Bernd. "Statistical relevance—relevant statistics, part I." EMBO Journal 34, no. 22 (September 21, 2015): 2727–30. http://dx.doi.org/10.15252/embj.201592958.

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Il'ya, Matveev, Savchenko Dmitrii, and Ulyanova Vera. "Legal statistics and the statistical jurisprudence." Ideas and Ideals 2, no. 4 (December 21, 2015): 51–58. http://dx.doi.org/10.17212/2075-0862-2015-4.2-51-58.

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Дисертації з теми "Statistics":

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Tauber, Vojtěch. "Vývoj právní úpravy postavení a organizace statistické služby v Československu 1918 - 1938." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-201593.

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This diploma thesis examines the legislation of the status and organisation of the statistical service in Czechoslovakia in the years 1918-1938 which has lacked sufficient exploration. In this period, statistics referring to public administration was centralised and under the responsibility of the State Statistical Council and the State Statistical Office. These institutions are given special attention, particularly issues associated with their intricate aspects: personnel, budget and location. While the State Statistical Office was one of the central government authorities in Czechoslovakia, the State Statistical Council had the nature of an advisory body and an independent decision-making authority. The centralisation did not apply to statistical surveys carried out by certain cities. This thesis uses primarily unpublished archive materials and published sources concerning the activities of the State Statistical Office and the State Statistical Council.
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Kazlauskienė, Aušra. "Pradinių klasių mokinių statistinių gebėjimų ugdymas." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2005. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2005~D_20050902_110922-16508.

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The problem of the research is systematic approach and accessibility of the content of developing statistical skills for primary school pupils. The content of developing elements of statistical skills and probability theory integrates pupils’ mathematical skills, knowledge of the content of other subjects, general skills of cognition and their personal experience, therefore it is a general problem of primary education; A system of items intended for teaching elements of statistics and probability theory is valid and accessible for pupils provided it covers: - technical skills of statistics (an ability to read and represent data); - skills of mathematical operations (to calculate the mean, classify data, round off numbers, grasp elements of probability theory, determine percentage of a number); - cognitive skills of the level accessible to pupils (ability to word a problem, define a hypothesis, compile data to verify the hypothesis, analyse and interpret data, draw conclusions). The premises for successful development of primary school pupils’ statistical skills are as follows: - development of primary school teachers’ statistical skills in the framework of their academic and continued education; - establishment of the content of developing statistical skills corresponding to international standards in the general curricula of the primary school; - provision of teaching statistics and probability theory elements based in the skills acquired in the primary school in the... [to full text]
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Holmberg, Anders. "Essays on Model Assisted Survey Planning." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3417.

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Marohn, Frank [Verfasser]. "On statistical information of extreme order statistics / Frank Marohn." Würzburg : Universität Würzburg, 2010. http://d-nb.info/1101947373/34.

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Obryant, Monique J. "How Attitudes towards Statistics Courses and the Field of Statistics Predicts Statistics Anxiety among Undergraduate Social Science Majors: A Validation of the Statistical Anxiety Scale." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc1011855/.

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The aim of this study was to validate an instrument that can be used by instructors or social scientist who are interested in evaluating statistics anxiety. The psychometric properties of the English version of the Statistical Anxiety Scale (SAS) was examined through a confirmatory factor analysis of scores from a sample of 323 undergraduate social science majors enrolled in colleges and universities in the United States. In previous studies, the psychometric properties of the Spanish and Italian versions of the SAS were validated; however, the English version of the SAS had never been assessed. Inconsistent with previous studies, scores on the English version of the SAS did not produce psychometrically acceptable values of validity. However, the results of this study suggested the potential value of a revised two-factor model SAS to measure statistics anxiety. Additionally, the Attitudes Towards Statistics (ATS) scale was used to examine the convergent and discriminant validities of the two-factor SAS. As expected, the correlation between the two factors of the SAS and the two factors of the ATS uncovered a moderately negative correlation between examination anxiety and attitudes towards the course. Additionally, the results of a structural regression model of attitudes towards statistics as a predictor of statistics anxiety suggested that attitudes towards the course and attitudes towards the field of statistics moderately predicts examination anxiety with attitudes towards the course having the greatest influence. It is recommended that future studies examine the relationship between attitudes towards statistics, statistics anxiety, and other variables such as academic achievement and instructional style.
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Wiberg, Marie H. "Computerized achievement tests : sequential and fixed length tests." Doctoral thesis, Umeå universitet, Statistiska institutionen, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-148.

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The aim of this dissertation is to describe how a computerized achivement test can be constructed and used in practice. Throughout this dissertation the focus is on classifying the examinees into masters and non-masters depending on their ability. However, there has been no attempt to estimate their ability. In paper I, a criterion-referenced computerized test with a fixed number of items is expressed as a statistical inference problem. The theory of optimal design is used to find the test that has the strongest power. A formal proof is provided showing that all items should have the same item characteristics, viz. high discrimination, low guessing and difficulty near the cutoff score, in order to give us the most powerful statistical test. An efficiency study shows how many times more non-optimal items are needed if we do not use optimal items in order to achieve the same power in the test. In paper II, a computerized mastery sequential test is examined using sequential analysis. The focus is on examining the sequential probability ratio test and to minimize the number of items in a test, i.e. to minimize the average sample number function, abbreviated as the ASN function. Conditions under which the ASN function decreases are examined. Further, it is shown that the optimal values are the same for item discrimination and item guessing, but differ for item difficulty compared with tests with fixed number of items. Paper III presents three simulation studies of sequential computerized mastery tests. Three cases are considered, viz. the examinees' responses are either identically distributed, not identically distributed, or not identically distributed together with estimation errors in the item characteristics. The simulations indicate that the observed results from the operating characteristic function differ significantly from the theoretical results. The mean number of items in a test, the distribution of test length and the variance depend on whether the true values of the item characteristics are known and whether they are iid or not. In paper IV computerized tests with both pretested items with known item parameters, and try-out items with unknown item parameters are considered. The aim is to study how the item parameters for try-out items can be estimated in a computerized test. Although the unknown examinees' abilities may act as nuisance parameters, the asymptotic variance of the item parameter estimators can be calculated. Examples show that a more reliable variance estimator yields much larger estimates of the variance than commonly used variance estimators.
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Hardy, James C. (James Clifford). "A Monte Carlo Study of the Robustness and Power Associated with Selected Tests of Variance Equality when Distributions are Non-Normal and Dissimilar in Form." Thesis, University of North Texas, 1990. https://digital.library.unt.edu/ark:/67531/metadc332130/.

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When selecting a method for testing variance equality, a researcher should select a method which is robust to distribution non-normality and dissimilarity. The method should also possess sufficient power to ascertain departures from the equal variance hypothesis. This Monte Carlo study examined the robustness and power of five tests of variance equality under specific conditions. The tests examined included one procedure proposed by O'Brien (1978), two by O'Brien (1979), and two by Conover, Johnson, and Johnson (1981). Specific conditions included assorted combinations of the following factors: k=2 and k=3 groups, normal and non-normal distributional forms, similar and dissimilar distributional forms, and equal and unequal sample sizes. Under the k=2 group condition, a total of 180 combinations were examined. A total of 54 combinations were examined under the k=3 group condition. The Type I error rates and statistical power estimates were based upon 1000 replications in each combination examined. Results of this study suggest that when sample sizes are relatively large, all five procedures are robust to distribution non-normality and dissimilarity, as well as being sufficiently powerful.
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Johnson, Eric P. "Composite strength statistics from fiber strength statistics." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/26420.

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Utilization of composites in critical design applications requires an extensive engineering experience data base which is generally lacking, especially for rapidly developing constituent fibers. As a supplement, an accurate reliability theory can be applied in design. This investigation is a part of a research effort to develop a probabilistic model of composite reliability capable of using data produced in small laboratory test samples to predict the behavior of large structures with respect to their actual dimensions. This work included testing of composite strength which was then used in exploring the methodology of predicting composite reliability from the parent single filament fiber strength statistics. This required testing of a coordinate set of test samples which consisted of a composite and its parent fibers. Previously collected fiber strength statistics from two different production spools were used in conjunction with the current effort. This investigation established that, for a well made composite, the Local Load Sharing Model of reliability prediction exhibited outstanding correlation with experimental data and was sufficiently sensitive to predict deficient composite strength due to a specific fiber spool with an abnormally weak lower tail. In addition, it provided an upper bound on the composite reliability. This investigation is unique in that is used a coordinate set of data with an unambiguous genesis of parent fiber and subsequent composite. The findings of this investigation are also definitive in that six orders of extrapolation of size in reliability prediction has been verified
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Lee, Yun-Soo. "On some aspects of distribution theory and statistical inference involving order statistics." Virtual Press, 1991. http://liblink.bsu.edu/uhtbin/catkey/834141.

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Statistical methods based on nonparametric and distribution-free procedures require the use of order statistics. Order statistics are also used in many parametric estimation and testing problems. With the introduction of modern high speed computers, order statistics have gained more importance in recent years in statistical inference - the main reason being that ranking a large number of observations manually was difficult and time consuming in the past, which is no longer the case at present because of the availability of high speed computers. Also, applications of order statistics require in many cases the use of numerical tables and computer is needed to construct these tables.In this thesis, some basic concepts and results involving order statistics are provided. Typically, application of the Theory of Permanents in the distribution of order statistics are discussed. Further, the correlation coefficient between the smallest observation (Y1) and the largest observation (Y,,) of a random sample of size n from two gamma populations, where (n-1) observations of the sample are from one population and the remaining observation is from the other population, is presented.
Department of Mathematical Sciences
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Kim, Woosuk. "Statistical Inference on Dual Generalized Order Statistics for Burr Type III Distribution." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1396533232.

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Книги з теми "Statistics":

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Mecke, Klaus R., and Dietrich Stoyan, eds. Statistical Physics and Spatial Statistics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45043-2.

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Jay, Bennett, ed. Statistics in sport. London: Arnold, 1998.

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Muth, James E. De. Basic statistics and pharmaceutical statistical applications. New York: Marcel Dekker, 1999.

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Muth, James E. De. Basic statistics and pharmaceutical statistical applications. Boca Raton: CRC Press, Taylor & Francis Group, 2014.

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Organization, Food and Agriculture, ed. World agricultural statistics: FAO statistical pocketbook. Rome: Food and Agriculture Organization, 1989.

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Communicable Disease Surveillance Centre of the Public Health Laboratory Service (Great Britain), Great Britain. Office of Population Censuses and Surveys., and Great Britain. Government Statistical Service., eds. Communicable disease statistics: 1986 statistical tables. London: H.M.S.O., 1988.

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Muth, James E. De. Basic statistics and pharmaceutical statistical applications. 2nd ed. Boca Raton, FL: Chapman & Hall/CRC, 2006.

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Thirkettle, G. L. Wheldon's business statistics and statistical method. 9th ed. London: Pitman, 1988.

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Marques de Sá, Joaquim P. Applied Statistics Using SPSS, STATISTICA and MATLAB. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05804-6.

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Joaquim P. Marques de Sá. Applied Statistics Using SPSS, STATISTICA and MATLAB. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003.

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Частини книг з теми "Statistics":

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Giorgio, Massimiliano. "Statistics for Experimental and Technological Research." In A Decade of Research Activities at the Department of Industrial Engineering (UniNa-DII), 137–44. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53397-6_8.

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AbstractThis chapter provides a synthetic overview of research activities and main outcomes of members of the scientific-disciplinary sector “SECS-S/02—Statistica per la Ricerca Sperimentale e Tecnologica” at the University of Naples Federico II, in the decade 2013–2023. Research activities of the group focus on modern statistical problems arising in the field of experimental sciences (statistics and probability calculus, design, and analysis of experiments), notably in engineering (reliability, statistical quality control). The main fields of application concern technology, safety, environment, territory, production processes, products, and natural resources.
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Iba, Y. "Bayesian Statistics and Statistical Mechanics." In Springer Series in Synergetics, 235–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-74554-6_60.

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Korotkevitch, Dmitri. "Statistics." In Pro SQL Server Internals, 55–80. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1964-5_3.

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Allen, Brandon, Latha Ganti, and Bobby Desai. "Statistics." In Quick Hits in Emergency Medicine, 123–24. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7037-3_20.

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Friese, Randall S. "Statistics." In Surgical Critical Care and Emergency Surgery, 436–42. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781118274231.ch46.

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Jacobs, Konrad. "Statistics." In Discrete Stochastics, 103–18. Basel: Birkhäuser Basel, 1992. http://dx.doi.org/10.1007/978-3-0348-8645-1_5.

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Muenchen, Robert A. "Statistics." In Statistics and Computing, 599–645. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0685-3_17.

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Caillol, Cécile. "Statistics." In Springer Theses, 39–53. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70650-4_3.

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Woodford, C., and C. Phillips. "Statistics." In Numerical Methods with Worked Examples: Matlab Edition, 231–48. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-1366-6_11.

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Williams, Michael. "Statistics." In Society Today, 204–9. London: Macmillan Education UK, 1986. http://dx.doi.org/10.1007/978-1-349-08845-4_42.

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Тези доповідей конференцій з теми "Statistics":

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Schield, Milo. "Statistical prevarication: telling half truths using statistics." In Statistics Education and the Communication of Statistics. International Association for Statistical Education, 2005. http://dx.doi.org/10.52041/srap.05404.

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All too often statistics are characterized as lies. But statistics are more likely to be half truths than lies. This paper studies statistical prevarication – the art of strad- dling both sides of an issue or idea – involving a statistic. This paper studies statis- tical prevarications in everyday use and in statistics education. If statistics educa- tors are to avoid a charge of statistical negligence, they should focus more on iden- tifying and eliminating sources of statistical prevarication in their teaching and textbooks. And statistical educators should do more to help students become statis- tically literate in detecting statistical prevarication.
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Nogales Vasconcelos, Ana, Cauan Braga da Silva Cardoso, and Isabella Figueiredo Vieira. "Learning to portray your reality: teaching statistics to high school students." In Advances in Statistics Education: Developments, Experiences, and Assessments. International Association for Statistical Education, 2015. http://dx.doi.org/10.52041/srap.15113.

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The Institutional Scientific Initiation Scholarship Program (PIBIC) “Learning to Portray Your Reality” seeks to motivate female high school students to apply for undergraduate program in statistics at the University of Brasilia (UnB), to divulge the undergraduate program in statistics at UnB and to promote the statistical education. The high school students learned how to have a statistical thinking, what is the job of a statistician and the roll of statistic in science, as well as some basics concepts of statistics. They also learned how to work with the database available online by the Brazilian Institute of Geography and Statistics (IBGE). Furthermore, it was designed an activity to promote the undergraduate program in statistics at UnB and the learning of the statistic in their school.
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Da Valle, Silvia, and Susi Osti. "“Statistica enigmistica”: An ISTAT puzzle magazine to introduce non-specialists to statistics through a ludic approach." In Promoting Understanding of Statistics about Society. International Association for Statistical Education, 2016. http://dx.doi.org/10.52041/srap.16201.

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Spreading the culture of data as a means of understanding and evaluating reality, and of making informed decisions, is one of the missions of Istat, the Italian National Institute of Statistics. Istat promotes statistical literacy also for non-professional audiences. Therefore, researchers’ efforts are aimed at finding appealing proposals to emphasize the importance of having statistical skills in every-day life. Recently, Istat created “Statistica enigmistica”: a puzzle magazine designed to play with concepts, definitions and data, and to encourage the use of the cognitive tools of Statistics when observing and comprehending society. The games have been designed to involve a wide audience, ranging from children to adults. The topics have been selected to offer an overview of the main statistical data regarding Italian society, and to give useful references for further insights.
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Gordon, Sue, Anna Reid, and Peter Petocz. "How important are communication skills for ‘good’ statistics students? — an international perspective." In Statistics Education and the Communication of Statistics. International Association for Statistical Education, 2005. http://dx.doi.org/10.52041/srap.05402.

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What do statistics teachers believe makes a good student of statistics? What part does the ability to communicate statistical results and ideas play in this judgement? In this paper, we investigate these questions and suggest answers based on a recent empirical study carried out by e-mail interview with IASE members from around the world. The responses alert us to the diversity of views on the relative importance of statistical communication held by statistics educators in service courses. Some teachers propose that communication skills are essential to learning statistics at university, others do not mention communication. In any discussion on statistical communication, we should be aware of the range of views held by statistics educators themselves, and the range of views that they communicate to students through their teaching.
5

Weldon, Larry. "From data to graphs to words - but where are the models?" In Statistics Education and the Communication of Statistics. International Association for Statistical Education, 2005. http://dx.doi.org/10.52041/srap.05206.

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The pioneers of statistics focused on parametric estimation and summary to communicate statistical findings. The tradition of basing inference on parametric fits is a central mode in statistics education, but in statistics applications, computer- based graphical summary is playing an increasingly important role. A parallel development has been the spread of statistics education to almost all disciplines, and thus the need to communicate statistical results to non-specialists has become more acute. These influences of more graphics and a wider distribution require adaptation in our statistics courses. This paper provides examples of, and arguments for, the use of simulation and graphical display, and the role of these techniques in enhancing the verbalization of analytical results. The immediate goal of the paper is to persuade those who design curricula for early statistics courses to provide a serious introduction to graphical data analysis, at the expense of some traditional parametric inference. The ultimate goal is to enable more students to communicate statistical findings effectively.
6

Ruiz, Leticia. "Statistical literacy hatching." In Statistics education for Progress: Youth and Official Statistics. International Association for Statistical Education, 2013. http://dx.doi.org/10.52041/srap.13902.

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In Mexico there are 22 million children and teenagers around 6 and 15 years old, who represent 29% of its population. The National Institute of Statistics and Geography in Mexico (INEGI) is looking forward to increase the use of statistic and geographic data in all society sectors. To achieve this goal, specially in people in the referred age, INEGI has established an agreement with the Ministry of Education, in charge of National Education for elementary and high school students, in order to include statistical and geographical information in all the available channels as text books, computer programs and videos. At the same time, INEGI offers a dedicated section in the institutional INEGI website. To close the circle, INEGI together with Aguascalientes’ Universty, developed a Statistical course, made specifically for elementary school teachers, to teach them on the large variety of information INEGI produces and how to link it with their syllabus.
7

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.
8

McGuinness, Gareth, and Lesley Hooper. "The role of national statistics institutions in the use and understanding of official statistics in the compulsory education sector." In Statistics Education and the Communication of Statistics. International Association for Statistical Education, 2005. http://dx.doi.org/10.52041/srap.05302.

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Statistics New Zealand, like many national statistics institutions (NSIs), is charged with increasing the use and understanding of official statistics in the wider community. This seemingly insignificant outcome is driving radical changes in the way NSIs communicate their statistics to their audiences. One area where NSIs are increasingly working to communicate statistics is the compulsory education sector. Helping primary and secondary school students use and understand statistics is regarded as one of the best ways to promote the long- term use and understanding of official statistics. While there are many ways to build this statistical capability in young people, an emerging policy strand suggests that it is not realistic for NSIs such as Statistics New Zealand to embark on statistical education programmes of their own. Instead, it is argued that they should focus on three planks: encouraging agencies for education policy to place a high value on statistics education; influencing curriculum development (in statistics and other subjects) to include significant official statistics components; and providing targeted official statistics resources to support curricular components. This paper critically examines this approach to achieving the desired relationship between NSIs and the compulsory education sector, from a New Zealand perspective.
9

Petocz, Peter, and Anna Reid. "Servicing students communicating ideas about statistics." In Statistics Education and the Communication of Statistics. International Association for Statistical Education, 2005. http://dx.doi.org/10.52041/srap.05401.

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Statistical communication has become a larger part of statistics pedagogy during the previous decade, particularly for those students who are majoring in the discipline. Students in servicing courses may have less opportunity to develop statistical communication skills, as they usually take only a small number of statistics subjects: it is this group that forms the basis of our present study. Based on analysis of the discourse in interview transcripts, we highlight an interesting disjunction: many students seem to be able to communicate their understanding of statistics to the interviewer, but their statements about their statistical communication imply that they are unaware that they are communicating statistically during this process. We briefly explore the pedagogical implications of our findings.
10

Smith, Wayne. "Statistics and the media." In Statistics Education and the Communication of Statistics. International Association for Statistical Education, 2005. http://dx.doi.org/10.52041/srap.05301.

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As a rule, it's fair to say that journalists and statisticians have little in common. Yet, journalists and national statistical agencies are virtually inseparable. Why? Because the general public is an important audience for national statistical agencies and the news media are a powerful tool for reaching this audience. Most journalists are uncomfortable with numbers: many are unable to calculate a percentage increase; many more would find it difficult to explain the difference between a percentage decline and a percentage point decline. Most probably find data boring. A journalist with specialized knowledge of statistics is a rarity. Statistics Canada, like most national statistical agencies, places great importance on communicating with the media. Our challenge is twofold: to engage the interest of journalists in our data and surreptitiously raise the level of their statistical literacy and to engage the interest of our statisticians in presenting statistics in a manner which the journalist, as a layperson, can understand. The paper will outline the various approaches that Statistics Canada has taken to meet this twofold challenge and will discuss our experiences in educating both journalists and statisticians to tell the story behind the numbers.

Звіти організацій з теми "Statistics":

1

David, H. A. Order Statistics and Nonparametric Statistics. Fort Belvoir, VA: Defense Technical Information Center, June 1992. http://dx.doi.org/10.21236/ada253574.

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2

David, H. A. Order Statistics and Nonparametric Statistics. Fort Belvoir, VA: Defense Technical Information Center, August 1985. http://dx.doi.org/10.21236/ada158499.

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3

Perfit, Janine, Mariko Russell, and Jorge E. Muñoz-Ayala. Improving the Quality of Statistics in Belize. Inter-American Development Bank, December 2014. http://dx.doi.org/10.18235/0009236.

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In modern public management the use of statistics for decision making is essential. Evidence-based policy, as well as results-based public management, cannot operate effectively without reliable and timely data. Likewise, without more specialized, quality statistics, the achievement of development objectives cannot be appropriately monitored, or the effectiveness of development plans evaluated. In the specific context of Belize, the importance of a well-functioning statistical system is essential to the process of economic and social development of the country. Yet, according to the evidence collected, the country is characterized by the absence of a statistical system; as such, the agencies that produce data based on administrative registries and surveys usually do their work independently; there is no regulation that governs statistical production in any institution outside the Statistical Institute of Belize (SIB); and there is no common set of classifiers, norms, and definitions based on good practices that meet international standards. Since the SIB does not audit and regulate the production of data in the country, statistical production is disintegrated and there is room for improvement in timeliness and quality. Moreover, Belize's National Statistical System (NSS) does not have any effective mechanism to reach users. To improve this situation, this technical note recommends strengthening the SIB's capacity to produce basic statistics and increasing the country's use of statistics through the implementation of a national statistics strategy in Belize with the SIB in the role as the coordinating agency. This will help to strengthen the entire statistical system.
4

Lurie, D., and R. H. Moore. Applying statistics. Test accounts, February 1994. http://dx.doi.org/10.2172/10145691.

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5

Wendelberger, Laura Jean. Image Statistics. Office of Scientific and Technical Information (OSTI), August 2017. http://dx.doi.org/10.2172/1374311.

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6

Mills, D. L. Statistics server. RFC Editor, February 1987. http://dx.doi.org/10.17487/rfc0996.

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7

Benson, P. Some statistics. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1992. http://dx.doi.org/10.4095/301727.

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8

McWilliams, William H., and Richard A. Birdsey. Midsouth timber statistics. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, 1986. http://dx.doi.org/10.2737/so-rb-108.

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9

Smith, W. Brad, and Mark F. Golitz. Indiana forest statistics. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station, 1988. http://dx.doi.org/10.2737/nc-rb-108.

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10

Kleven, Henrik. Sufficient Statistics Revisited. Cambridge, MA: National Bureau of Economic Research, May 2020. http://dx.doi.org/10.3386/w27242.

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