937 resultados para Statistical methodologies


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In the current study, we evaluated various robust statistical methods for comparing two independent groups. Two scenarios for simulation were generated: one of equality and another of population mean differences. In each of the scenarios, 33 experimental conditions were used as a function of sample size, standard deviation and asymmetry. For each condition, 5000 replications per group were generated. The results obtained by this study show an adequate type error I rate but not a high power for the confidence intervals. In general, for the two scenarios studied (mean population differences and not mean population differences) in the different conditions analysed, the Mann-Whitney U-test demonstrated strong performance, and a little worse the t-test of Yuen-Welch.

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The identifiability of the parameters of a heat exchanger model without phase change was studied in this Master’s thesis using synthetically made data. A fast, two-step Markov chain Monte Carlo method (MCMC) was tested with a couple of case studies and a heat exchanger model. The two-step MCMC-method worked well and decreased the computation time compared to the traditional MCMC-method. The effect of measurement accuracy of certain control variables to the identifiability of parameters was also studied. The accuracy used did not seem to have a remarkable effect to the identifiability of parameters. The use of the posterior distribution of parameters in different heat exchanger geometries was studied. It would be computationally most efficient to use the same posterior distribution among different geometries in the optimisation of heat exchanger networks. According to the results, this was possible in the case when the frontal surface areas were the same among different geometries. In the other cases the same posterior distribution can be used for optimisation too, but that will give a wider predictive distribution as a result. For condensing surface heat exchangers the numerical stability of the simulation model was studied. As a result, a stable algorithm was developed.

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In terms of soil fertility, zinc is a micronutrient that is very important in the culture of soy, maize, rice and coffee, because it is a structural and functional component of a great number of enzymes. Therefore, diverse methods have been used to determine zinc in soil. In this work we use colorimetry as a methods of zinc determination in soil using two methodologies of sample digesting, H2SO4/H2O2 and HNO3/H2O2. In order to compare the results, atomic absorption spectrometry (AAS) was used. Results show that colorimetric methods can be used due to good sensitivity and reproducibility, since the zinc calibration curve showed good linearity. Comparing colorimetric methods with AAS we observed that the results were equivalent, as proven by the statistical values of the F and t of Student tests. Furthermore, both methods of soil digesting can be used, leading to a flexible methodology of low-cost for routine zinc analyses in soil.

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This paper analyses the international inequalities in CO2 emissions intensity for the period 1971- 2009 and assesses explanatory factors. Multiplicative, group and additive methodologies of inequality decomposition are employed. The first allows us to clarify the separated role of the carbonisation index and the energy intensity in the pattern observed for inequalities in CO2 intensities; the second allows us to understand the role of regional groups; and the third allows us to investigate the role of different fossil energy sources (coal, oil and gas). The results show that, first, the reduction in global emissions intensity has coincided with a significant reduction in international inequality. Second, the bulk of this inequality and its reduction are attributed to differences between the groups of countries considered. Third, coal is the main energy source explaining these inequalities, although the growth in the relative contribution of gas is also remarkable. Fourth, the bulk of inequalities between countries and its decline are explained by differences in energy intensities, although there are significant differences in the patterns demonstrated by different groups of countries.

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In this work, the effectiveness of four screening techniques (three techniques of the diffusion method and one microdilution broth method) were compared. Evaluated were the ethanolic and dichloromethanic extracts of Miconia rubiginosa (Melastomataceae) against six standard bacteria (ATCC). The results showed statistical disagreement among the three diffusion techniques. Among the diffusion techniques, the well technique displayed the best result. However the microdilution broth method demonstrated to be the most adequate method to evaluate the antibacterial activity of plant crude extracts and pure compounds when compared to the other methodologies.

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A statistical mixture-design technique was used to study the effects of different solvents and their mixtures on the yield, total polyphenol content, and antioxidant capacity of the crude extracts from the bark of Schinus terebinthifolius Raddi (Anacardiaceae). The experimental results and their response-surface models showed that ternary mixtures with equal portions of all the three solvents (water, ethanol and acetone) were better than the binary mixtures in generating crude extracts with the highest yield (22.04 ± 0.48%), total polyphenol content (29.39 ± 0.39%), and antioxidant capacity (6.38 ± 0.21). An analytical method was developed and validated for the determination of total polyphenols in the extracts. Optimal conditions for the various parameters in this analytical method, namely, the time for the chromophoric reaction to stabilize, wavelength of the absorption maxima to be monitored, the reference standard and the concentration of sodium carbonate were determined to be 5 min, 780 nm, pyrogallol, and 14.06% w v-1, respectively. UV-Vis spectrophotometric monitoring of the reaction under these conditions proved the method to be linear, specific, precise, accurate, reproducible, robust, and easy to perform.

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We explore a DNA statistical model to obtain information about the behavior of the thermodynamics quantities. Special attention is given to the thermal denaturation of this macromolecule.

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Marine traffic is expected to increase rapidly in the future, both in the Baltic Sea and in the Gulf of Finland. As the number of vessels in the area increases, so does the risk of serious marine accidents. To help prevent such accidents in the future, the International Maritime Organization (IMO) has put forth the International Safety Management Code (the ISM Code), which aims to improve the safety of the vessels. The second work package of the Development of maritime safety culture (METKU) project investigates the effects of the ISM Code and potential areas of improvement in maritime safety. The first phase in the work package used a literature review to determine how maritime safety culture could be improved. Continuous improvement, management commitment and personnel empowerment and motivation were found to be essential. In the second phase, shipping companies and administrators were interviewed. It was discovered that especially incident reporting based on continuous improvement was felt to be lacking. This third phase aims to take a closer look at incident reporting and suggest improvements based on the findings. Both the IMO and national legislation encourage shipping companies in incident reporting, and on the national level a shared incident reporting system (ForeSea) is being pushed forward. The objective of this research project was to find out the IMO’s attitude towards incident reporting, to establish a theoretical framework of reference in incident reporting, and to observe how reporting is actually being employed on the seas. Existing incident reporting systems were also researched. The study was carried out using a literature review and the results previously gathered in interviews. The results of phase two were elaborated further for themes relating to incident reporting. According to the findings of this research, the theoretical background of incident reporting dates back to the early 20th century. Although some theories are widely accepted, some have also received criticism. The lack of a concise, shared terminology poses major difficulties in maritime incident reporting and in determining its efficiency. A central finding is the fact that existing incident reporting focuses mostly on information flow away from the ship, whereas the backward information flow is much less planned and monitored. In incident reporting, both nationally and internationally, stakeholders are plenty. The information produced by these parties is scattered, however, and thus not very usable. Based on this research, the centralizing of this information should be made a priority. Traditionally, the success of incident reporting has been determined statistically, from the number of reported incidents. Yet existing reporting systems have not been designed with such statistical analysis in mind, so different methodologies might yield a more comprehensive view. The previous findings of seafarers and management (including shipping companies and administration) having differing views on safety work and safety management were backed up by the results of this study. Seafarers find seamanship and storytelling important, while management wants a more systematic and broad approach on safety matters. The research project was carried out by the Centre for Maritime Studies of the University of Turku, in the Kotka unit (Maritime Logistics Research), with coordination by the Kotka Maritime Research Centre. The major financiers of the project were the European Union and the city of Kotka. The financing authority was the Regional Council of Päijät-Häme. Partners in the project were the shipping companies Finnlines Oyj, Kristina Cruises Oy, Meriaura Oy and VG-Shipping Oy, and the ports of Helsinki, Kotka and Hamina. The partners provided both funding for the project and information for the research.

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The prevailing undergraduate medical training process still favors disconnection and professional distancing from social needs. The Brazilian Ministries of Education and Health, through the National Curriculum Guidelines, the Incentives Program for Changes in the Medical Curriculum (PROMED), and the National Program for Reorientation of Professional Training in Health (PRO-SAÚDE), promoted the stimulus for an effective connection between medical institutions and the Unified National Health System (SUS). In accordance to the new paradigm for medical training, the Centro Universitário Serra dos Órgãos (UNIFESO) established a teaching plan in 2005 using active methodologies, specifically problem-based learning (PBL). Research was conducted through semi-structured interviews with third-year undergraduate students at the UNIFESO Medical School. The results were categorized as proposed by Bardin's thematic analysis, with the purpose of verifying the students' impressions of the new curriculum. Active methodologies proved to be well-accepted by students, who defined them as exciting and inclusive of theory and practice in medical education.

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Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

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ABSTRACT This study aimed to develop a methodology based on multivariate statistical analysis of principal components and cluster analysis, in order to identify the most representative variables in studies of minimum streamflow regionalization, and to optimize the identification of the hydrologically homogeneous regions for the Doce river basin. Ten variables were used, referring to the river basin climatic and morphometric characteristics. These variables were individualized for each of the 61 gauging stations. Three dependent variables that are indicative of minimum streamflow (Q7,10, Q90 and Q95). And seven independent variables that concern to climatic and morphometric characteristics of the basin (total annual rainfall – Pa; total semiannual rainfall of the dry and of the rainy season – Pss and Psc; watershed drainage area – Ad; length of the main river – Lp; total length of the rivers – Lt; and average watershed slope – SL). The results of the principal component analysis pointed out that the variable SL was the least representative for the study, and so it was discarded. The most representative independent variables were Ad and Psc. The best divisions of hydrologically homogeneous regions for the three studied flow characteristics were obtained using the Mahalanobis similarity matrix and the complete linkage clustering method. The cluster analysis enabled the identification of four hydrologically homogeneous regions in the Doce river basin.

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Earnings management (EM) literature examines managers’ use of judgment in financial reporting and in structuring transactions to alter financial reports for a specific reason. Mainstream EM literature strongly concentrates on statistical research methodologies and it is driven by positive accounting theory. Although EM occurs in the process of preparing corporate financial reports, that process has so far largely remained a “black box” in prior literature. The purpose of this study is to analyze what EM is, how and why it unfolds and how it is intertwined in the process of preparing corporate financial reports. In order to meet the needs of the study, a qualitative case study method will be used. The contribution of this study is threefold. First, it indicates that the concept of EM is not as unam-biguous as the prior literature has assumed. I find that EM is socially constructed and more open to interpretation than absolutely dichotomous conception given by previous studies. Second, this study contributes to our knowledge of the role and the importance of actors involved in conducting EM, indicating that EM is much more actor-dependent than the prior literature has assumed. Third, this study broadens our knowledge base with regard to the processes and potential for EM in academic research.

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Longitudinal surveys are increasingly used to collect event history data on person-specific processes such as transitions between labour market states. Surveybased event history data pose a number of challenges for statistical analysis. These challenges include survey errors due to sampling, non-response, attrition and measurement. This study deals with non-response, attrition and measurement errors in event history data and the bias caused by them in event history analysis. The study also discusses some choices faced by a researcher using longitudinal survey data for event history analysis and demonstrates their effects. These choices include, whether a design-based or a model-based approach is taken, which subset of data to use and, if a design-based approach is taken, which weights to use. The study takes advantage of the possibility to use combined longitudinal survey register data. The Finnish subset of European Community Household Panel (FI ECHP) survey for waves 1–5 were linked at person-level with longitudinal register data. Unemployment spells were used as study variables of interest. Lastly, a simulation study was conducted in order to assess the statistical properties of the Inverse Probability of Censoring Weighting (IPCW) method in a survey data context. The study shows how combined longitudinal survey register data can be used to analyse and compare the non-response and attrition processes, test the missingness mechanism type and estimate the size of bias due to non-response and attrition. In our empirical analysis, initial non-response turned out to be a more important source of bias than attrition. Reported unemployment spells were subject to seam effects, omissions, and, to a lesser extent, overreporting. The use of proxy interviews tended to cause spell omissions. An often-ignored phenomenon classification error in reported spell outcomes, was also found in the data. Neither the Missing At Random (MAR) assumption about non-response and attrition mechanisms, nor the classical assumptions about measurement errors, turned out to be valid. Both measurement errors in spell durations and spell outcomes were found to cause bias in estimates from event history models. Low measurement accuracy affected the estimates of baseline hazard most. The design-based estimates based on data from respondents to all waves of interest and weighted by the last wave weights displayed the largest bias. Using all the available data, including the spells by attriters until the time of attrition, helped to reduce attrition bias. Lastly, the simulation study showed that the IPCW correction to design weights reduces bias due to dependent censoring in design-based Kaplan-Meier and Cox proportional hazard model estimators. The study discusses implications of the results for survey organisations collecting event history data, researchers using surveys for event history analysis, and researchers who develop methods to correct for non-sampling biases in event history data.

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The objective of this research is to demonstrate the use of Lean Six Sigma methodology in a manufacturing lead time improvement project. Moreover, the goal is to develop working solutions for the target company to improve its manufacturing lead time. The theoretical background is achieved through exploring the literature of Six Sigma, Lean and Lean Six Sigma. The development will be done in collaboration with the related stakeholders, by following the Lean Six Sigma improvement process DMAIC and by analyzing the process data from the target company. The focus of this research is in demonstrating how to use Lean Six Sigma improvement process DMAIC in practice, rather than in comparing Lean Six Sigma to other improvement methodologies. In order to validate the manufacturing system’s current state, improvement potential and solutions, statistical tools such as linear regression analysis were used. This ensured that all the decisions were as heavily based on actual data as possible. As a result of this research, a set of solutions were developed and implemented in the target company. These solutions included batch size reduction, bottleneck shift, first-in first-out queuing and shifting a data entry task from production planners to line workers. With the use of these solutions, the target company was able to reduce its manufacturing lead time by over one third.