This study investigates whether financial globalization influences emerging markets by examining the correlation between a global market in relation to emerging markets. By constructing yearly correlation coefficients through collecting daily return from index markets, financial contagion can be detected. International trade serves as a measurement for financial globalization, in the context of the continuation of globalization in the world. Through the progress of creating the correlation coefficients, the significance of trade globalization has been identified along with the relationship the correlation coefficients have with it. Leading to the conclusion that financial globalization does impact the emerging markets and have done so throughout the timespan of 25 years.

We define and study multivariate and matrix variate skew Pearson type VII and skew t-distributions. We derive the marginal and conditional distributions, the linear transformation, and the stochastic representations of the multivariate and matrix variate skew Pearson type VII distributions and skew t-distributions. Also, we study the limiting distributions.

The purpose of this study was to explore the relationships between and among various demographic and test score data with American College Testing (ACT) scores in 281 Tennessee high schools. This study also addressed which high school characteristics were related to the number of students meeting the ACT requirement for Tennessee lottery scholarships. In addition, this study examined Tennessee Value Added Assessment System's (TVAAS) assessment of ACT scores and its distribution of grades to Tennessee's high schools based upon its Value-Added analysis. The researcher performed correlations and multivariable linear regressions using socioeconomic status, ethnicity, dropout rate, graduation rate, attendance, average daily membership, per-pupil expenditure, teacher salary, Gateway exams, English I scores, and math foundations scores as independent variables and ACT scores as the dependent variable. The strengths of the correlations were examined and the best combination of independent variables was used to predict future ACT scores. Schools were divided into quartiles, based upon average daily membership and attendance rates, in order to analyze the differences in r2 values among the quartiles when running regressions to predict ACT scores. Quartiles, based upon the percentage of students qualifying for free/reduced meals, ethnicity, and average daily membership were used to study the difference in TVAAS' grade distribution based upon its assessment of ACT scores. The findings indicated that English I and II scores are most strongly associated with ACT composite scores including the four ACT subtests: math, English, reading, and science. English scores were found to be more strongly associated with ACT math scores than Algebra I scores and more strongly associated with ACT science scores than biology scores. It was found that the 21 composite ACT score requirements of Tennessee's lottery scholarships predominantly favored Caucasian students who did not qualify for free/reduced-priced meals. It was also discovered that TVAAS' ACT grades were unevenly distributed when schools were divided into quartiles based upon the percentage of students qualifying for free/reduced-priced meals, ethnicity, and average daily membership. Only one school in the quartile containing the schools with the highest percentage of students qualifying for free/reduced-priced meals scored above the state's average gain in the reading section of the ACT test.

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摘要 皮爾森相關係數通常作為描述區間尺度變數間相關性的參考指標，然而在社會科學領域中，由於資料多數以順序尺度的形式呈現，因此藉由傳統的皮爾森相關係數來描述順序尺度資料間的相關性通常會導致某種程度的誤差。儘管如此，以往的文獻多數傾向支持以等距離分數來取代順序尺度資料，並直接計算皮爾森相關係數。藉由模擬實驗的結果，我們發現這樣的作法並非在所有情況下都合理。 此外本研究中也對多序類相關係數進行探討。就表示順序變數間相關性的準確程度而言，多序類相關係數明顯優於利用等距離分數來計算皮爾森相關係數的方法；但若以操作上的便利程度而言，後者仍具有其優勢。 關鍵字：順序尺度、皮爾森相關係數、多序類相關係數。 / Abstract Pearson correlation coefficient is typically used to describe the correlation between two interval-scaled variables. In social science, however, most of the data are represented in ordinal-scale, and hence describing the correlation between two ordinal-scaled variables in terms of Pearson correlation coefficient would inevitably result in certain errors. Though the practice is deemed acceptable and generally supported in literatures, we found, through intensive simulations, that it should be executed with care. Polychoric correlation coefficient was also investigated. In order to describe the correlation between two ordinal-scaled variables, we found, in terms of the degree of accuracy, that Polychoric correlation coefficient is definitely better than Pearson correlation coefficient with equal-distance scores. Pearson correlation coefficient, on the other hands, is much easier to calculate, and should not be totally ignored. Key words：Ordinal-scale、Pearson correlation coefficient、Polychoric correlation coefficient。

The objective of this thesis is to proof possibilities to use data from the electronic revenue records to measure the visit rate and process recommendations for the use in tourism. The thesis focuses on the tourism sector. Concepts and related terminology are explained. Described in this thesis are sources of the information about visitors, profiles of visitors, decision-making process about visits, and selected technologies used to measure the visit rate. Reasons, problems and classification related to measurements of the visit rate are included in the thesis as well. The practical part examines the use of information from electronic revenue records for the purpose of measuring the number of visitors based on the calculation of Pearson's correlation coefficients. The principal how EET functions is explained in the thesis. Significant part of the work is the analysis of daily and monthly revenues of electronic records in the sector of lodging in regions of the Czech Republic. Based on this analysis, 6 groups are determined in which the development of daily seasonality takes place in a specific way. An important part is also the calculation of average cost of accommodation in regions, which identifies certain economic impacts of tourism. Part of the thesis are summarized recommendations for the use of data from EET.

Neste trabalho foi analisada a influência de um evento sobre o mercado de ações brasileiro a partir das redes, e suas árvores geradoras mínimas, obtidas de medidas de dependência baseadas nas correlações de Pearson, de Spearman e de Kendall. O evento considerado foi a notícia da noite de 17 de maio de 2017 em que o dono da empresa brasileira JBS, Joesley Batista, gravou o então Presidente da República Michel Temer autorizando a compra do silêncio de um Deputado Federal. O dia seguinte a notícia, 18 de maio de 2017, foi definido como o dia do evento. Foram coletados dados de alta frequência de 58 ações do Ibovespa no período de 11 a 25 de maio de 2017. As alterações nas redes das ações do mercado foram analisadas comparando-se o período anterior e posterior ao evento em duas escalas de tempo: (1) Redes diárias: cinco pregões antes do evento, o dia do evento e, cinco pregões depois do evento, com cotações a cada 15 minutos; (2) Agrupadas em antes e depois: agrupando os dados dos 5 dias antes e dos 5 dias depois do evento. O estudo das redes diárias indicou mudança de tendência nas suas propriedades no decorrer do período que contém o evento, com cotações a cada 15 minutos. Isto sugeriu que análise do efeito médio contido nos dados agrupados antes de depois do evento poderiam tornar mais evidente as mudanças na estrutura de rede das ações. As redes antes e depois do evento apresentaram mudanças significativas nas suas métricas que ficaram mais evidenciadas nas árvores geradoras mínimas. As redes geradas pelas correlações de Kendall e Spearman apresentaram um número maior de agrupamentos antes e depois do evento e, após o evento, as árvores geradoras mínimas apresentaram uma redução do número de agrupamentos de ações para todos os tipos de correlação. As distribuições de grau ponderado após o evento indicam uma probabilidade maior de vértices com graus distante da média. As métricas das árvores geradoras mínimas por correlação de Spearman sofreram a maior variação, seguidas pelas de Kendall e Pearson, e também, indicaram que as redes após o evento ficaram mais robustas, ou seja, mais rígidas. A maior robustez das redes após o evento indica maior conectividade do mercado, tornando-o, como um todo, mais suscetível ao impacto de novos acontecimentos. / In this work the influence of an event on the Brazilian stock market was analyzed from networks and its minimum spanning trees obtained from measures of dependence based on the Pearson, Spearman, and Kendall\'s correlations. The event considered was the news in the evening of May 17, 2017 in which the owner of the Brazilian company JBS, Joesley Batista, recorded the Brazilian President Michel Temer authorizing the purchase of the silence of a congress member. The day just after the news, May 18, 2017, was defined as the event day. High-frequency data from 58 Ibovespa shares were collected from 11 to 25 May 2017. Changes in the stocks networks were analyzed comparing the period before and after the event in two time scales: (1) Daily networks: five trade sections before the event, the day of the event and, five trade sections after the event, with price every 15 minutes; (2) Grouped before and after do evento: grouping data from 5 days before and 5 days after event. The study of the daily networks indicated a change of trend in their properties during the period that contains the event, with quotations every 15 minutes. The study of daily networks indicated a change of trend in their properties during the period containing the event. This suggested that analysis of the mean effect of grouped data before and after the event could highlight the changes in the network structure. The networks before and after the event showed significant changes in their metrics, which became more evident from the minimum spanning trees. After the event, the minimum spanning trees for grouped data got a smaller number of clusters in the networks for all kind of correlations. The networks generated by Kendall and Spearman correlations presented a larger number of clusters before and after the event. The weighted degree distributions after the event suggest a power law decay tail for all the correlations considered and indicates a higher probability of vertices with weighted degrees far away from the mean weighted degree. The minimum spanning tree metrics generated by Spearman correlation suffered the greatest variation, followed by those of Kendall and Pearson; and their values indicates that after the event the networks became more robust, that is, more rigid. The increase in the networks robustness after the event indicates a higher market connectivity, making it as a whole, more susceptible to the impact of new events.

Made available in DSpace on 2016-04-28T14:16:45Z (GMT). No. of bitstreams: 1 Katia Regina Venturineli.pdf: 1419356 bytes, checksum: 17281fa74cf50df79adf93f85c3755fa (MD5) Previous issue date: 2010-05-13 / Karl Pearson (1857-1937) is usually known for his contribution to mathematics and statistics. Besides, he presented (1901-1902) a proposal to Biology: The homotyposis principle. He applied the statistics to test it. Pearson´s proposal generated an argument with William Bateson (1861-1926) and other biologists. This dissertation´s aim is, firstly, to describe Pearson´s proposal in relation to homotyposis in accordance with both biology and statistics terms, and then, to analyse it. It should also check if the negative reception by the Mendelians and other biologists was due to a weak basis. This dissertation contains an introduction and four chapters. Chapter 1 discusses some Karl Pearson´s previous statistical studies. Chapter 2 is about his career and professional interests dealing with biological aspects in relation to homotyposis. Chapter 3 analyses Pearson´s statistical concepts and its correlation verified in his homotyposis studies. Chapter 4 presents some conclusions about what was discussed in the previous chapters. This study showed that Pearson applied adequate methods accurately regarding statistics, such as collection, counting, tabulation, calculation and comparison of data according to the data studied. Nevertheless, the conception of homotyposis, its starting point in biological terms, was mistaken / Karl Pearson (1857-1936) é geralmente conhecido por suas contribuições relacionadas à matemática e estatística. Entretanto, além disso, ele apresentou (em 1901 e 1902) uma proposta em relação à biologia: o princípio da homotipose. Para testá-lo, ele aplicou a estatística. A proposta de Pearson gerou uma discussão com William Bateson (1861-1926) e outros biólogos da época. O objetivo desta dissertação é inicialmente descrever a proposta de Pearson relativa ao princípio da homotipose tanto em termos biológicos como em termos estatísticos e, a seguir, analisá-la. Procurará averiguar se a recepção negativa por parte dos mendelianos e outros biólogos se deveu a uma fundamentação fraca. Esta dissertação contém uma introdução e quatro capítulos. O capítulo 1 discute alguns precedentes dos estudos estatísticos de Karl Pearson. O capítulo 2 trata da carreira e interesses profissionais abordando os aspectos biológicos relacionados à homotipose. O capítulo 3 analisa os conceitos estatísticos de Pearson e as correlações verificadas em seus estudos sobre homotipose. O capítulo 4 apresenta algumas considerações finais sobre o que foi discutido nos capítulos anteriores. Este estudo mostrou que na parte relacionada à estatística Pearson empregou de modo adequado métodos como coleta, contagem, tabulação, cálculo e comparação de dados estudados. Apesar disso, a concepção da homotipose, seu ponto de partida, em termos biológicos, era equivocada

Matrix variate skew elliptically contoured distributions generalize several classes of important distributions. This paper defines and explores matrix variate skew elliptically contoured distributions. In particular, we discuss the first two moments of the matrix variate skew elliptically contoured distributions.