Tato diplomová práce se zabývá Weibullovými modely, přesněji dvouparametrickým Weibullovým rozdělením. Práce se zabývá odhady parametrů, a to čtyřmi variantami kvantilové metody, metodou maximální věrohodnosti a grafickou metodou Weibullova pravděpodobnostního grafu. Je uvedeno odvození odhadu parametrů pro jednovýběrovou analýzu rozptylu pro Weibullovo rozdělení. Jsou zde odvozeny vztahy pro model s konstantním parametrem alfa, s konstantním parametrem beta a s oběma konstantními parametry. Také jsou uvedeny testové statistiky pro rušivé parametry - skórový test, Waldův test a test založený na věrohodnostním poměru. V poslední kapitole je provedena aplikace jednotlivých představených metod. Srovnání metod je ukázáno pomocí grafů, histogramů a tabulek. Metody jsou naprogramovány v~softwaru R. Jejich funkčnost a vlastnosti jsme ověřili na dvou simulovaných souborech dat. Diplomová práce je zakončena příkladem tří simulovaných náhodných výběrů, na kterých byla provedena analýza pomocí zavedených metod.

Master of Science / Department of Psychological Sciences / Patrick Knight / The current study examined attributions of blame for workplace errors through the lens of Kelley’s (1967) ANOVA model of attribution-making, which addresses the consensus, consistency, and distinctiveness of a behavior. Consensus and distinctiveness information were manipulated in the description of a workplace accident. It was expected that participants would make different attributions regarding the cause of the event due to these manipulations. This study further attempted to determine if an individual’s core self-evaluations (CSE) impact how she or he evaluates a workplace accident and attributes blame, either from the perspective of the employee who made the error or that of a co-worker. Because CSE are fundamental beliefs about an individual’s success, ability, and self-worth, they may contribute to how the individual attributes blame for a workplace accident. It was found that CSE were positively related to participants’ inclination to make internal attributions of blame for a workplace error. Contrary to expectations, manipulations of the consensus and distinctiveness of the workplace error did not moderate participants’ attributions of blame. Explanations for these findings are discussed, as are possible applications of this research.

Master of Landscape Architecture / Landscape Architecture/Regional and Community Planning / Brent Chamberlain / Streets and sidewalks are important public places for a wide variety of activities, such as social interaction and physical activities. Public spaces can provide numerous benefits, such as physical, psychological, social, spiritual, and aesthetic wellbeing; in order to maximize these benefits effective planning and design is critical. However, there is a need to increase empirical data which can support good planning for these public spaces. The purpose of this research study is to better understand how different elements of streetscape design influence a person’s preferences for the design of the space. A streetscape consists of a variety of different infrastructure and natural forms, which are combined together to create a space centered on the movement of people. A survey was conducted with the aims to better understand how key design elements may influence users’ preferences with regard to safety and attractiveness. The project study site is Moro Street in Aggieville Business District in Manhattan, KS. The study and survey were developed using the psychophysical approach, which employed a quantitative methods to analyze the perceptions of Aggieville patrons. The research methods consists of four main parts: variable selection, streetscape design, public survey, and data analysis. An ANOVA was conducted that revealed statistically significant effects related to the preference for streetscape design in terms of safety and attractiveness, as well as a combined average evaluation. Evidence shows that the on street parking (Parking) and green infrastructure (Green Infrastructure) are statistically significant (p < .05), whereas seating and biking had no statistically significant effect on the evaluation of attractiveness. Also, the on street parking (Parking), green infrastructure (Green Infrastructure) and bike lane (biking)are statistically significant (p < .05), whereas seating had no statistically significant effect on the evaluation of safety. Overall, on street parking (Parking) and green infrastructure (Green Infrastructure) are statistically significant (p < .05), whereas seating and biking had no statistically significant effect on the evaluation of both safety and attractiveness. These results support previous work from environmental psychologists, and provide additional empirical evidence to support effective street design.

This document proposes a study to ascertain if a relationship exists between levels of child and parent anxiety symptoms during an intervention designed to decrease anxiety in youth. This document systemically describes family variables related to anxiety in youth at the individual, parent-child, marital, whole family, and extra familial subsystem levels, in addition to previous research analyzing parental anxiety and the direction of change between child and parent anxiety during youth-focused interventions. The study involves gathering anxiety symptom data from parent and child participants at 14 time points and analyzing it using dependent samples t-test, regression, and ANOVA repeated measure analyses. These analyses serve to answer the research questions of whether child and parent anxiety symptoms improve in a youth-focused CBT intervention for anxiety from pre- to post-treatment, whether there exists a significant relationship between the severity of anxiety symptoms in youth and parents surrounding a youth-focused anxiety intervention, and whether this relationship is consistent. / text

The aim of this master thesis project was to statistically correlate various powder characteristics to the quality of additively manufactured parts. An additional goal of this project was to find a potential second source supplier of powder for GKN Aerospace Sweden in Trollhättan. Five Inconel® alloy 718 powders from four individual powder suppliers have been analyzed in this project regarding powder characteristics such as: morphology, porosity, size distribution, flowability and bulk properties. One powder out of the five, Powder C, is currently used in production at GKN and functions as a reference. The five powders were additively manufactured by the process of laser metal deposition according to a pre-programmed model utilized at GKN Aerospace Sweden in Trollhättan. Five plates were produced per powder and each cut to obtain three area sections to analyze, giving a total of fifteen area sections per powder. The quality of deposited parts was assessed by means of their porosity content, powder efficiency, geometry and microstructure. The final step was to statistically evaluate the results through the analysis methods of Analysis of Variance (ANOVA) and simple linear regression with the software Minitab. The method of ANOVA found a statistical significant difference between the five powders regarding their experimental results. This made it possible to compare the five powders against each other. Statistical correlations by simple linear regression analysis were found between various powder characteristics and quality of deposited part. This led to the conclusion that GKN should consider additions to current powder material specification by powder characteristics such as: particle morphology, powder porosity and flowability measurements by a rheometer. One powder was found to have the potential of becoming a second source supplier to GKN, namely Powder A. Powder A had overall good powder properties such as smooth and spherical particles, high particle density at 99,94% and good flowability. The deposited parts with Powder A also showed the lowest amount of pores compared to Powder C, a total of 78 in all five plates, and sufficient powder efficiency at 81,6%.

Analysis of variance (ANOVA) is a robust test against the normality assumption, but it may be inappropriate when the assumption of homogeneity of variance has been violated. Welch ANOVA and the Kruskal-Wallis test (a non-parametric method) can be applicable for this case. In this study we compare the three methods in empirical type I error rate and power, when heterogeneity of variance occurs and find out which method is the most suitable with which cases including balanced/unbalanced, small/large sample size, and/or with normal/non-normal distributions.

在資訊較不對稱的不動產市場中，購屋者往往無法有效的利用資訊正確預期房價走勢，而過去的研究多半是以總體經濟變數或是市場環境因素探討購屋者實際的預期，並沒有太多購屋者預期的個體研究。近年來行為財務學的文獻中已經發現個人特質以及身分背景將影響投資人的決策模式，故本研究希望從個體角度出發，研究購屋者是否因個人特質、身分背景或是從業性質影響房價預期的正確性？而在台灣的主要城市中，影響的程度與方向有何不同？ 由於購屋者對房價預期正確與否為一機率變數，因此本研究使用二元羅吉特模型估計之。實證結果顯示，當購屋者最高學歷為碩士或碩士以上畢業時，其購屋時對於房價預期的正確機率顯著較高；另外每當購屋決策者之家庭月收入越高時，其預測房價的正確機率也顯著較高。

In this dissertation, we consider the problem of partitioning a set of k population with respect to a control population. For this problem some multistage methodologies are proposed and their properties are derived. Using the Monte Carlo simulation techniques, the small and moderate sample size performance of the proposed procedure are studied. We have also considered at statistical surveillance of various cancers in Louisiana.

Os anti-inflamatórios não esteroidais (AINEs) são a classe de medicamentos mais comumente utilizada na rotina clínica e cirúrgica de animais de companhia. Além de reduzirem a inflamação, possuem propriedades analgésicas e antipiréticas. O uso indiscriminado e a exposição acidental aos AINEs associados com a hipotensão gerada pela anestesia geral são situações que podem contribuir para o surgimento de lesões renais agudas e isquêmicas. Desta forma, o presente trabalho objetivou o emprego de modelagem matemática baseada na Lógica Fuzzy para análise do comportamento renal em cadelas submetidas a cirurgias eletivas e tratadas com anti-inflamatórios apresentando diferente seletividade de ação de inibição das Cicloxigenases. O emprego da Lógica Fuzzy surge como alternativa para resolver incertezas que não conseguem ser expressas prelos modelos matemáticos existentes, minimizando possíveis erros ao modelar o comportamento de cada indivíduo envolvido no processo, realizando uma análise mais precisa e fiel a realidade, não descartando as subjetividades de cada animal, sendo para a medicina veterinária uma ferramenta para pesquisadores e especialistas no desenvolvimento de um diagnóstico adequado. O estudo ocorreu no Hospital Veterinário da Unijuí. Para o desenvolvimento desse projeto foram utilizados três grupos (10 animais cada) de cães, fêmeas, hígidas, submetidas à Ovariohisterectomia eletiva e tratadas durante três dias (no dia do procedimento cirúrgico e dois dias pós-cirúrgico) à base de AINEs. Durante o período experimental, foram realizadas análises laboratoriais para a detecção de injúria renal, bem como provas de função renal (ureia, creatinina, gama-glutamil-transpeptidase urinária e urinálise). Posteriormente a coleta dos dados realizou-se a modelagem matemática, partindo dos resultados obtidos para avaliar o dano renal em relação ao medicamento através da Cicloxigenase. Através do uso da análise de variância e do teste de médias constatou-se que para os diferentes protocolos AINES ocorreu pouca variação entre si, apresentando maior variação apenas da variável Ureia Sérica, além de, comprovarmos que as únicas variáveis com significância em relação ao tempo para serem utilizadas em um modelo matemático são a GGT urinária e Creatinina Urinária. Partindo dessas variáveis é possível, através de um Sistema Baseados em Regras Fuzzy (SBRF), simular o comportamento dessas duas variáveis comparando-as entre si, onde conseguimos 13 encontrar valores que quando comparados aos obtidos através nos exames de sangue e urina, mostram-se muito semelhantes, demonstrando assim que pode ser um auxiliar para determinar uma possível lesão renal. / 57 f.

This thesis presents a contribution to the active research area of functional data analysis (FDA) and is concerned with the analysis of data from complex experimental designs in which the responses are curves. High resolution, closely correlated data sets are encountered in many research fields, but current statistical methodologies often analyse simplistic summary measures and therefore limit the completeness and accuracy of conclusions drawn. Specifically the nature of the curves and experimental design are not taken into account. Mathematically, such curves can be modelled either as sample paths of a stochastic process or as random elements in a Hilbert space. Despite this more complex type of response, the structure of experiments which yield functional data is often the same as in classical experimentation. Thus, classical experimental design principles and results can be adapted to the FDA setting. More specifically, we are interested in the functional analysis of variance (ANOVA) of experiments which use orthogonal designs. Most of the existing functional ANOVA approaches consider only completely randomised designs. However, we are interested in more complex experimental arrangements such as, for example, split-plot and row-column designs. Similar to univariate responses, such complex designs imply that the response curves for different observational units are correlated. We use the design to derive a functional mixed-effects model and adapt the classical projection approach in order to derive the functional ANOVA. As a main result, we derive new functional F tests for hypotheses about treatment effects in the appropriate strata of the design. The approximate null distribution of these tests is derived by applying the Karhunen- Lo`eve expansion to the covariance functions in the relevant strata. These results extend existing work on functional F tests for completely randomised designs. The methodology developed in the thesis has wide applicability. In particular, we consider novel applications of functional F tests to gait analysis. Results are presented for two empirical studies. In the first study, gait data of patients with cerebral palsy were collected during barefoot walking and walking with ankle-foot orthoses. The effects of ankle-foot orthoses are assessed by functional F tests and compared with pointwise F tests and the traditional univariate repeated-measurements ANOVA. The second study is a designed experiment in which a split-plot design was used to collect gait data from healthy subjects. This is commonly done in gait research in order to better understand, for example, the effects of orthoses while avoiding confounded analysis from the high variability observed in abnormal gait. Moreover, from a technical point of view the study may be regarded as a real-world alternative to simulation studies. By using healthy individuals it is possible to collect data which are in better agreement with the underlying model assumptions. The penultimate chapter of the thesis presents a qualitative study with clinical experts to investigate the utility of gait analysis for the management of cerebral palsy. We explore potential pathways by which the statistical analyses in the thesis might influence patient outcomes. The thesis has six chapters. After describing motivation and introduction in Chapter 1, mathematical representations of functional data are presented in Chapter 2. Chapter 3 considers orthogonal designs in the context of functional data analysis. New functional F tests for complex designs are derived in Chapter 4 and applied in two gait studies. Chapter 5 is devoted to a qualitative study. The thesis concludes with a discussion which details the extent to which the research question has been addressed, the limitations of the work and the degree to which it has been answered.