The study's purpose was to identify demographics, educational background, finances, formal and informal education and experiences, reading habits, external environmental factors, psychological factors, and computer efficacy factors that predict a student's ability to successful complete an online (Web-based) distance learning community college course. Major student retention theories and student attrition and persistence research guided the study. Distance learners (N = 926) completed four surveys, which collected data for 26 predictor variables that included age, gender, marital status, ethnicity, support others, course load, first-time student, last semester attended, student type and location, financial stability, tuition payment, prior learning experiences, reading habits, family support, enrollment encouragement, study encouragement, time management, study environment, employment, extrinsic and intrinsic motivation, locus of control, self-efficacy, computer confidence and skills, and number of prior online courses. Successful or unsuccessful course completion was the dependent variable. Statistical analyses included Cronbach's alpha, Pearson chi-square, two-sample t test, Pearson correlation, phi coefficient, and binary logistic regression. Variables in each factor were entered sequentially in a block using separate binary logistic regression models. Statistically significant variables were course load, financial stability, prior learning experiences, time management and study environment, extrinsic motivation, self-efficacy, and computer skills. Selected predictor variables (N = 20) were entered hierarchically in a logistic regression model of which course load, financial stability, and self-efficacy were statistically significant in the final block. Correlation coefficients were computed for statistically significant predictor variables to determine whether the significance was confined to the control group or an overall level of significance. Findings were supported through cross-validation and forward stepwise entry of variables in logistic regression. Despite having two or more at-risk factors, distance learners who had high levels of self-efficacy, good computer and time management skills, financial stability, a favorable study environment, were enrolled in more than one course, and believed their prior learning experiences helped prepared them for their course were more likely to be successful.

In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available for the built-up areas along rural highways. Due to high fatalities in rural highways, it is important to identify the factors that cause the vehicle crashes. The main objective of this study is to determine the factors associated with severities of crashes that occurred in built-up areas along the rural highways of Nevada. Those factors could aid in making informed decisions while setting up speed zones in these built-up areas. Using descriptive statistics and binary logistic regression model, 337 crashes that occurred in 11 towns along the rural highways from 2002 to 2010 were analyzed. The results showed that more crashes occurred during favorable driving conditions, e.g., 87% crashes on dry roads and 70% crashes in clear weather. The binary logistic regression model showed that crashes occurred from midnight until 4 a.m. were 58.3% likely to be injury crashes rather than property damage only crashes, when other factors were kept at their mean values. Crashes on weekdays were three times more likely to be injury crashes than that occurred on weekends. When other factors were kept at their mean value, crashes involving motorcycles had an 80.2% probability of being injury crashes. Speeding was found to be 17 times more responsible for injury crashes than mechanical defects of the vehicle. As a result of this study, the Nevada Department of Transportation now can take various steps to improve public safety, including steps to reduce speeding and encourage the use of helmets for motorcycle riders.

This thesis investigates the factors that are associated with annual changes in the share price of Johannesburg Stock Exchange (JSE) listed companies. In this study, an increase in value of a share is when the share price of a company goes up by the end of the financial year as compared to the previous year. Secondary data that was sourced from McGregor BFA website was used. The data was from 2004 up to 2011. Deciding which share to buy is the biggest challenge faced by both investment companies and individuals when investing on the stock exchange. This thesis uses binary logistic regression to identify the variables that are associated with share price increase. The dependent variable was annual change in share price (ACSP) and the independent variables were assets per capital employed ratio, debt per assets ratio, debt per equity ratio, dividend yield, earnings per share, earnings yield, operating profit margin, price earnings ratio, return on assets, return on equity and return on capital employed. Different variable selection methods were used and it was established that the backward elimination method produced the best model. It was established that the probability of success of a share is higher if the shareholders are anticipating a higher return on capital employed, and high earnings/ share. It was however, noted that the share price is negatively impacted by dividend yield and earnings yield. Since the odds of an increase in share price is higher if there is a higher return on capital employed and high earning per share, investors and investment companies are encouraged to choose companies with high earnings per share and the best returns on capital employed. The final model had a classification rate of 68.3% and the validation sample produced a classification rate of 65.2% / Mathematical Sciences / M.Sc. (Statistics)

In the present study, I analyze adolescent girls’ smoking through a unique combination of a quantitative survey of impressions and a theoretical analysis based on new elaborations of Bourdieu’s concept symbolic capital. The method of the study is three-fold. First, focus-group interviews elicit relevant impressions of adolescents in the eyes of peers. Second, a questionnaire survey distributed to adolescent peers quantitatively investigates how impressions of a girl on a picture differ depending on whether or not she has a cigarette. Third, a theoretical analysis based on elaborations of Bourdieu’s theories scrutinizes the results of the questionnaire survey. The results of the questionnaire survey indicate that smoking adolescent girls generate impressions of being significantly less likable, more popular, more conceited, less kind, less shy, more liable to bully, less funny, more deceitful, and less compassionate than non-smoking adolescent girls. In the elaborations of Bourdieu’s theories, I introduce a division of symbolic capital into two forms: symbolic virtue capital, generated through impressions of virtues, and symbolic power capital, generated through intimidating impressions of destructive power. According to the theoretical analysis of the results, smoking adolescent girls have relatively much symbolic power capital but relatively little symbolic virtue capital compared to adolescent girls that do not smoke.

Doctor of Philosophy / Department of Physics / Dean Zollman / As part of a collaborative study of the science preparation of elementary school teachers, we investigated the quality of students’ reasoning and explored the relationship between sophistication of reasoning and the degree to which the courses were considered inquiry oriented. To probe students’ reasoning, we developed open-ended written content questions with the distinguishing feature of applying recently learned concepts in a new context. We devised a protocol for developing written content questions that provided a common structure for probing and classifying students’ sophistication level of reasoning. In designing our protocol, we considered several distinct criteria, and classified students’ responses based on their performance for each criterion. First, we classified concepts into three types: Descriptive, Hypothetical, and Theoretical and categorized the abstraction levels of the responses in terms of the types of concepts and the inter-relationship between the concepts. Second, we devised a rubric based on Bloom’s revised taxonomy with seven traits (both knowledge types and cognitive processes) and a defined set of criteria to evaluate each trait. Along with analyzing students’ reasoning, we visited universities and observed the courses in which the students were enrolled. We used the Reformed Teaching Observation Protocol (RTOP) to rank the courses with respect to characteristics that are valued for the inquiry courses. We conducted logistic regression for a sample of 18 courses with about 900 students and reported the results for performing logistic regression to estimate the relationship between traits of reasoning and RTOP score. In addition, we analyzed conceptual structure of students’ responses, based on conceptual classification schemes, and clustered students’ responses into six categories. We derived regression model, to estimate the relationship between the sophistication of the categories of conceptual structure and RTOP scores. However, the outcome variable with six categories required a more complicated regression model, known as multinomial logistic regression, generalized from binary logistic regression. With the large amount of collected data, we found that the likelihood of the higher cognitive processes were in favor of classes with higher measures on inquiry. However, the usage of more abstract concepts with higher order conceptual structures was less prevalent in higher RTOP courses.

IPCC於第四次報告書中，模擬氣候持續暖化預測未來海平面上升之情形，而海平面上升對於人口集中的台北都會區將產生莫大之衝擊，同時亦會造成土地利用變遷。本研究目的在於探討海平面上升對台北都會區土地利用變遷之影響，以及受淹沒地區之人口未來可能之遷移區位，主要係從社會經濟發展層面進行分析。運用二元羅吉斯迴歸模式並結合土地利用轉換與影響模型（CLUE-s），以四種不同情境模擬土地利用變遷之情況，其情境分別為海平面上升59公分管制農林地與不管制，以及海平面上升100公分管制農林地與不管制。 　　研究結果顯示，海平面上升之情形越嚴重，未來的都市建地發展會越趨向擴張的形式，對農林地產生變遷之壓力；而於同一海平面上升水平下，針對農林地進行管制，其建地之發展會較為集中於都市計畫地區範圍內，且多數人口亦將遷移至此，容易形成人口壓力。此外，土地利用變遷模擬所得之新增建地部分，於情境A、C下足以容納受影響之人口，但情境B、D則不足以容納，皆會對台北都會區產生容受力之問題，產生累計人口超過計畫人口之現象。因此，建議未來政府於都市發展上，可調整都市計畫內之土地使用強度或都市範圍，也可利用都市更新之方式減少新的土地開發；此外，從國家層級分析，未來的國土計畫法於立法上，亦可將更多氣候變遷相關影響因子納入四大功能分區，透過適宜性分析進行分類分級，以做為未來土地利用發展之引導。 / The 4th IPCC report simulated climate warming and predicted future sea-level rise scenarios. A sea level rise will have a great impact on the population of the Taipei metropolitan area, and it will also produce land-use changes. The purpose of this study is to research the impact of sea level change on land use changes and population migration in Taipei metropolitan, and the areas that will be immigrated by the flooded areas. The method used includes binary logistic regression model combined with Conversion of Land Use and its Effects Model (CLUE-s). Setting the sea-level rise and regulating agricultural land, forest land of the four simulated situations. The results show that the higher sea level rises, the more transformation towards urban development in the future, and the higher sea level will also pressure agriculture and forestry changes. As a result of population pressure on Taipei metropolitan area, the same level of sea-level rise for the regulation of agriculture and forestry land, the development of building sites and population migration will be more concentrated on urban planning areas. In addition, the simulation of land use change generated new building sites, sufficient enough to accommodate the affected population under A and C simulated situations, but B and D couldn’t generate such results. Instead, it will generate a carrying capacity issue. Therefore, this thesis suggests that the government adjust the intensity of land use in urban development, urban areas and urban renewal of urban planning. In addition, the analysis from the national level, the future legislation of Land Planning Act should include the relation of climate change impact factors as a consideration of future land use development.

2007年美國爆發次級房貸違約潮造成了其經濟、房市和股市的不景氣，也波及到持有美國房貸證券化商品的各國，使其承受重大的損失，因此房屋抵押貸款違約的影響因素和金融資產證券化機制對貸款違約風險的影響又再度成為不動產與金融市場上之重要議題。而以往針對美國次貸危機的研究多指出道德風險是造成此次危機的原因之一，但是較缺乏實證研究的支持。 有鑑於此，本研究以我國的台北市和新北市的房屋抵押貸款市場作為研究對象，探討逆選擇和道德風險這兩個資訊不對稱的問題對貸款違約率的影響。研究結果顯示「貸款成數高、貸款利率高、搭配信貸和設定二胎的貸款比較容易違約」，證實逆選擇和道德風險問題確實存在於房屋抵押貸款市場，而且會增加貸款違約的機率。為了降低違約機率，從降低資訊不對稱的角度來看，本研究建議：一、建立全國房貸資料庫；二、將信貸的金額納入房貸的貸款成數中考慮，以降低款人的道德風險。 再者，本研究認為造成次貸危機的根本原因是不當政策導致的保證機制浮濫，以及高風險的房貸證券化商品的氾濫。為了避免我國發生類似次貸危機的事件，從減少資訊不對稱的角度切入，本研究建議我國的金融資產證券化機制應該：一、將道德風險內部化，消除創始機構自利的動機以減少道德風險；二、使用外部信用增強的方式，以確實發揮分散證券風險的作用。 / The 2007 subprime mortgage crisis has severely struck the stability of the worldwide financial markets. Some researches indicate that moral hazard problems are the main factors causing the crisis. However, few studies support asymmetry problems existing in a mortgage market by empirical evidences. First, using the mortgage samples from Taipei City and New Taipei City this study would like to understand if the mortgage market are information asymmetry problems, adverse selection and moral hazard, and conduct the empirical analysis for these factors’ impact on mortgage default. The results show that mortgage default is influenced significantly by the Loan-to-Value （LTV） ratio, contract interest rates, the existence of second liens and credit loans, and jobs. It shows that adverse selection and moral hazard actually exist in the mortgage market. According to the empirical results, secondly, this study proposes suggestions for mortgage lending and financial asset securitization to reduce adverse selection and moral hazard problems and enhance the regulation environment and market’s stability. It is expected that the results of this study will be applied to avoid the occurrence of similar crisis in Taiwan.

逆物流回收的複雜度遠比正向物流高，企業為專注核心價值多半將逆物流活動委外專業物流服務供應商。對第三方逆物流業者而言，選擇適當的回收處理中心位址為其重要核心能力之一，而現今研究對於選址模式中之回收不確定性，大多以歷史資料作為參數，無根據區域特性不同而有所分別。故本研究希望探討在零售商提供資訊的情境下，結合消費者問卷建構廢棄產品的使用年限機率、並以二元迴歸邏輯分析建構回收機率以此預測區域回收數量，透過資訊分享以建立更好的回收處理中心選址設置模式，使第三方逆物流業者可按照此模式選擇最適當的回收點位置與回收處理量安排用以求得利潤最大化。 / Since reverse logistics is much more complex than forward logistics, third-party logistics providers are often the prior choice for firms to obtain their core value when a reverse logistic activity is needed. For third-party logistics providers, the location is one of their crucial core values; while most of them can only rely on historical data to assume the best location, due to the uncertainty of recycling in present studies.Therefore, this paper tries to construct the probability of products’ used-years by combining the retailers’ information with consumer-oriented questionnaires. Binary logistic regression is the methodology used to analyze and predict recycling probability. By information-sharing the third-party logistics providers will be able to construct a better selecting model for the best facility location, which will reach the most suitable recycling quantity to maximize their profits.

永續發展的概念現今已被運用於都市，其中，都市綠地在環境、生態、景觀、社會各層面之機能皆可提升都市永續性，在快速的都市化下，都市內綠地減少，土地利用變遷帶來之環境衝擊影響已自個體單元累積到全球。然而，過去研究中未有關注在綠地的變化趨勢與其他土地利用間的互動關係，以及在不同區域下的變化差異。因此，本研究採用GIS和景觀指數看在1995年至2006年間台北都會區綠地變遷趨勢，並分區探討土地利用間的互動關係，最後藉由二元羅吉斯迴歸分析綠地變化可能原因。 研究結果顯示，在1995年至2006年間，台北都會區整體發展是建地增加，林地也呈上升趨勢，而草地是土地利用轉移下被犧牲掉最多的土地，綠地轉移成其他土地利用情形以都會邊緣地區最嚴重。不同綠地型態在1995年至2006年間的變遷仍有差異，林地在整個台北都會區屬於景觀中的基質，主導性未受動搖，僅在都會中心減少並受破壞；而農地面積略微下降，呈破碎化發展，尤其以都會中心外圍區農地被破壞情形最明顯；草地面積亦下降，破碎化情形較農地更嚴重，在都會郊區、次中心之草地被破壞嚴重，草地各方面機能降低。透過二元羅吉斯迴歸分析發現自然環境、社會經濟與計畫環境皆影響台北都會區的綠地變遷。根據研究結果，建議未來政府於都市計畫上應將綠地空間納入考量，對於不同綠地型態應有不同管制措施，考量各區域綠地型態之差異性，以及自然環境、社會經濟和計畫環境對於綠地變遷的影響，以促進都市朝向永續發展。 / The concept of sustainable development has been applied in cities. Urban green space plays an important role in enhancing the sustainability of the city in regards to the environment, ecology, landscape and society aspects. Under rapid urbanization, green space has greatly declined in cities. Environmental impact resulting from land use change has grown from local to global proportions. However, researches did not pay attention to interactions between green spaces and other land-use change trends or different types of change in different areas. This research used GIS and landscape metrics to investigate the green space change trend and interactions among different land use types in the Taipei metropolitan area from 1995 to 2006. Furthermore, this research analyzed possible reasons that may have caused green space change through logistic regression. The results showed that, from 1995 to 2006, the built up area and the forest increased in Taipei Metropolitan Area; however, the grass decreased because of land use change. Urban fringe was the place that green space changed to other land-use most. There were differences of land use change for different types of green space. Forest was the matrix in the landscape of Taipei metropolitan area. It still kept the predominant role, only decreased and was destroyed in the center of metropolitan area. Farmland slightly decreased and became fragmented, especially in the periphery of the urban center. Grassland area decreased and became fragmented much more than farmland. In suburb and sub-center, grassland was destroyed seriously and became less functional. Through binary logistic regression, the study found that natural environment, socio-economic and government planning do have influence on green space changes in the Taipei metropolitan area. According to the result of the study, the recommendation was that government should take green space into consideration when doing urban planning. For different types of green space and different areas, the government needs to have different measures and needs to consider the impact factors of green space change in order to accelerate sustainable development in cities.

Cultural competence is widely recognized as an essential strategy for reducing health disparities. As the United States' population becomes increasingly ethno-culturally diverse, these disparities are becoming even more pronounced. One particular challenge in this regard concerns overweight/obesity prevalence among American adults, as a disproportionately high number of racial and ethnic minority adults are classified as overweight or obese. Dietary behavior assessments are often utilized by health and human services professionals to obtain the data necessary to promote goals such as the reduction and elimination of overweight/obesity across all ethno-cultural groups. The primary objective of this research study was to develop, test, and evaluate a culturally-competent dietary behavior assessment instrument by effectively synthesizing qualitative methods from Cognitive Anthropology with appropriate survey research and quantitative statistical methods. Specifically, a quantitative methods triangle of hierarchical cluster analysis, binary logistic regression, and Poisson regression in conjunction with the free listing qualitative research technique from Cognitive Anthropology was explored as a possible combined methodological approach for researchers and public health professionals wishing to develop a comprehensive understanding of dietary behaviors at the local community level. Binary logistic regression and Poisson regression enabled the relationship between selected food categories and certain demographic/cultural indicators to be modeled, while hierarchical cluster analyses enabled modeling of the distinct patterns of food category groupings that comprise individuals' regular diet. Additionally, initial qualitative analyses of the raw data promoted an understanding of the influence that the local fast food and dine-in restaurant environment has on the dietary behaviors of the target population. The results of this study suggest that a quantitative methods triangle of hierarchical cluster analysis, binary logistic regression analysis, and Poisson regression analysis founded upon qualitative research principles has potential for use as a combined methodological approach for researchers and public health professionals wishing to develop a comprehensive understanding of dietary behaviors at the local community level. By employing these techniques, researchers can analyze individual dietary behaviors and eating patterns from a multifaceted perspective. In turn, public health professionals can develop community-based, cross-culturally relevant programs and interventions that are equally effective across all ethno-cultural groups in their target population.