994 resultados para statistical software


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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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O principal objetivo de um Planeamento de Experiências reside essencialmente na procura de relações entre variáveis e na comparação de níveis de fatores, recorrendo ao tratamento estatístico dos dados recolhidos. A utilização de blocos no Planeamento de Experiências é fundamental, pois permite reduzir ou eliminar a variabilidade introduzida por fatores que podem influenciar a experiência mas que não interessam e/ou não foram explicitamente incluídos durante o planeamento. Neste trabalho apresentamos os resultados do estudo e investigação dos Planos em Blocos Incompletos Equilibrados (BIBD), Planos em Blocos Incompletos Equilibrados com repetição de blocos (BIBDR) e Planos em Blocos Incompletos com blocos de diferentes dimensões (VBBD). Exploramos algumas propriedades e métodos de construção destes planos e ilustramos, sempre que possível, com exemplos. Tendo como base o planeamento em blocos, apresentamos uma aplicação dos BIBDR na área da Educação com o objetivo de comparar cinco domínios do pensamento algébrico de uma amostra de alunos do 1º ano do ensino superior em Cabo Verde. Para a análise dos dados da amostra foi utilizado o software R, versão 2.12.1. Pudemos constatar que existem diferenças significativas entre alguns dos domínios do pensamento algébrico, nomeadamente entre os domínios da Generalização da Aritmética e Tecnicismo Algébrico com os restantes domínios. Recomendamos a escolha de uma amostra mais representativa constituída por alunos de todas as instituições superiores de Cabo Verde.

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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The main purpose of an Experimental Design resides mainly in the search for relationships between variables and in comparing levels of factors, using statistical treatment of collected data. The use of blocks in Experimental Design is essential because it allows reducing or eliminating the variability introduced by factors that can influence the experience but are not of main interest and/or were not explicitly included during experiments. In this work we present the results of the study and research of Balanced Incomplete Block Designs (BIBD), Balanced Incomplete Block Designs with repeated blocks (BIBDR) and the Incomplete Blocks Designs with blocks with different dimensions (VBBD). We explore some properties and construction methods of such designs and illustrate, when possible, with examples. Based on Block Designs, we present an application of BIBDR in Education, with the aim of comparing five domains of algebraic thinking in a sample of 1st year students of higher education in Cape Verde. For the analysis of sample data, the software R was used, version 2.12.1. We observed that significant differences exist between some of the domains of algebraic thinking, especially among the domains of Generalization of Arithmetic and Algebraic Technicality with the remaining areas. For a more representative sample, we recommend a bigger sample consisting of students from all higher institutions of Cape Verde.

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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Iowa Individual Income Tax Statistical Report 2006

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The main purpose of an Experimental Design resides mainly in the search for relationships between variables and in comparing levels of factors, using statistical treatment of collected data. The use of blocks in Experimental Design is essential because it allows reducing or eliminating the variability introduced by factors that can influence the experience but are not of main interest and/or were not explicitly included during experiments. In this work we present the results of the study and research of Balanced Incomplete Block Designs (BIBD), Balanced Incomplete Block Designs with repeated blocks (BIBDR) and the Incomplete Blocks Designs with blocks with different dimensions (VBBD). We explore some properties and construction methods of such designs and illustrate, when possible, with examples. Based on Block Designs, we present an application of BIBDR in Education, with the aim of comparing five domains of algebraic thinking in a sample of 1st year students of higher education in Cape Verde. For the analysis of sample data, the software R was used, version 2.12.1. We observed that significant differences exist between some of the domains of algebraic thinking, especially among the domains of Generalization of Arithmetic and Algebraic Technicality with the remaining areas. For a more representative sample, we recommend a bigger sample consisting of students from all higher institutions of Cape Verde.

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O presente relatório inclui os resultados do estudo dos Sectores de Actividades da Embaixada de Cabo Verde em Portugal. Este trabalho decorreu em três etapas essências. A primeira foi leitura de um Manual de Procedimentos sobre a “Concepção e Implementação de um Sistema Administrativo e de Controlo Orçamental. A segunda centrou-se no Sector Administrativo, onde foram aplicados conhecimentos estatísticos nas diversas actividades realizadas. A última centrou-se no sector da Tesouraria e Contabilidade, onde adquiri conhecimentos básicos sobre o sector financeiro. O relatório encontra–se estruturado em 5 capítulos: O capítulo I fornece, de um modo sintético, uma panorâmica histórica da Embaixada de Cabo Verde em Portugal. O capítulo II, tem um carácter descritivo, ou seja descreve sumáriamente, os diversos sectores de actividades. As mais variadas actividades que giram em torno do Serviço Administrativo e Financeiro, justificaram um tratamento detalhado no capítulo III. A questão da comunidade cabo-verdiana, residente em Portugal, os softwares de Contabilidade Primavera, e Gestão de Requisição são abordadas no capítulo IV, sendo analisado o posicionamento da população de origem cabo-verdiana que reside em Portugal, aplicando certos casos e exemplos nos próprios softwares. O capítulo V sintetiza e conjuga as principais conclusões parcelares que foram apresentadas nos diversos capítulos, incluindo também limitações e trabalho futuro. Por fim está organizado um conjunto de anexos compostos por: documentos da Embaixada, glossário financeiro, e scrip do software “R”, que serviram de suporte ao estudo.

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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Revenue management (RM) is a complicated business process that can best be described ascontrol of sales (using prices, restrictions, or capacity), usually using software as a tool to aiddecisions. RM software can play a mere informative role, supplying analysts with formatted andsummarized data who use it to make control decisions (setting a price or allocating capacity fora price point), or, play a deeper role, automating the decisions process completely, at the otherextreme. The RM models and algorithms in the academic literature by and large concentrateon the latter, completely automated, level of functionality.A firm considering using a new RM model or RM system needs to evaluate its performance.Academic papers justify the performance of their models using simulations, where customerbooking requests are simulated according to some process and model, and the revenue perfor-mance of the algorithm compared to an alternate set of algorithms. Such simulations, whilean accepted part of the academic literature, and indeed providing research insight, often lackcredibility with management. Even methodologically, they are usually awed, as the simula-tions only test \within-model" performance, and say nothing as to the appropriateness of themodel in the first place. Even simulations that test against alternate models or competition arelimited by their inherent necessity on fixing some model as the universe for their testing. Theseproblems are exacerbated with RM models that attempt to model customer purchase behav-ior or competition, as the right models for competitive actions or customer purchases remainsomewhat of a mystery, or at least with no consensus on their validity.How then to validate a model? Putting it another way, we want to show that a particularmodel or algorithm is the cause of a certain improvement to the RM process compared to theexisting process. We take care to emphasize that we want to prove the said model as the causeof performance, and to compare against a (incumbent) process rather than against an alternatemodel.In this paper we describe a \live" testing experiment that we conducted at Iberia Airlineson a set of flights. A set of competing algorithms control a set of flights during adjacentweeks, and their behavior and results are observed over a relatively long period of time (9months). In parallel, a group of control flights were managed using the traditional mix of manualand algorithmic control (incumbent system). Such \sandbox" testing, while common at manylarge internet search and e-commerce companies is relatively rare in the revenue managementarea. Sandbox testing has an undisputable model of customer behavior but the experimentaldesign and analysis of results is less clear. In this paper we describe the philosophy behind theexperiment, the organizational challenges, the design and setup of the experiment, and outlinethe analysis of the results. This paper is a complement to a (more technical) related paper thatdescribes the econometrics and statistical analysis of the results.

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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The primary purpose of this brief is to provide various statistical and institutional details on the development and current status of the public agricultural research system in Cape Verde. This information has been collected and presented in a systematic way in order to inform and thereby improve research policy formulation with regard to the Cape Verdean NARS. Most importantly, these data are assembled and reported in a way that makes them directly comparable with the data presented in the other country briefs in this series. And because institutions take time to develop and there are often considerable lags in the agricultural research process, it is necessary for many analytical and policy purposes to have access to longer-run series of data. NARSs vary markedly in their institutional structure and these institutional aspects can have a substantial and direct effect on their research performance. To provide a basis for analysis and cross-country, over-time comparisons, the various research agencies in a country have been grouped into five general categories; government, semi-public, private, academic, and supranational. A description of these categories is provided in table 1.