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Articles 211 - 240 of 2693
Full-Text Articles in Statistics and Probability
Three Essays On Energy Related To State Policies And Low Carbon Transitions, Pinky Thomas
Three Essays On Energy Related To State Policies And Low Carbon Transitions, Pinky Thomas
Graduate Theses, Dissertations, and Problem Reports (ETD)
This dissertation consists of three essays on energy-related state policies and energy transition. Each paragraph below refers to the three abstracts for the three chapters in this dissertation, respectively.
The first essay is entitled: “Impacts of State Tax and Resource Ownership Policies on Extraction: Evidence from U.S. Natural Gas Production”. The innovation of combined use of horizontal drilling and hydraulic fracturing technologies during the 2000s has allowed natural gas producers in the United States to extract natural gas and liquids from deep shale formations in a cost-efficient manner. This essay evaluates whether unconventional gas production responds to tax changes, and …
Measuring The Performance Of Sdgs In Provincial Level Using Regional Sustainable Development Index, Nurafiza Thamrin, Ika Yuni Wulansari, Puguh Bodro Irawan
Measuring The Performance Of Sdgs In Provincial Level Using Regional Sustainable Development Index, Nurafiza Thamrin, Ika Yuni Wulansari, Puguh Bodro Irawan
Journal of Environmental Science and Sustainable Development
Measuring the national and sub-national progress in achieving such globally adopted development agendas as Sustainable Development Goals (SDGs) is particularly challenging due to data availability and compatibility of indicators to measure SDGs, especially in Indonesia. This paper attempts to measure the performance of sustainable development at the regional level in Indonesia by newly constructing a multidimensional composite index called the Regional Sustainable Development Index (RSDI). RSDI comprises four dimensions, covering comprehensive economic, social, environmental, and governance indicators. By applying factor analysis, the paper assesses the uncertainty of RSDI and the sensitivity of its composing indicators, then further investigates the relationship …
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Journal of Nonprofit Innovation
Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.
Imagine Doris, who is …
Challenges And Countermeasures For Treatment And Remediation Of Contaminated Mega-Sites In China, Xiaoyong Liao, Yixuan Hou, You Li, Tianyi Wang
Challenges And Countermeasures For Treatment And Remediation Of Contaminated Mega-Sites In China, Xiaoyong Liao, Yixuan Hou, You Li, Tianyi Wang
Bulletin of Chinese Academy of Sciences (Chinese Version)
The treatment and remediation of pollution at contaminated mega-sites poses a significant challenge in the environmental science both domestically and internationally. Contaminated mega-sites are characterized by their widespread impact, multiple types of pollutants, and significant ecological and environmental threats. The environmental behavior cognition and efficient remediation at contaminated mega-sites face enormous challenges, among which key technological issues such as the formation mechanism of soil and groundwater pollution, accurate identification of pollution sources, and intelligent decision-making optimization urgently need to be solved. In China, contaminated mega-sites are concentrated in economically developed regions such as Beijing-Tianjin-Hebei, the Yangtze River Economic Belt, and …
Atmospheric 14Co2 Observation: A Novel Method To Evaluate Carbon Emissions, Zhenchuan Niu, Peng Wang, Shugang Wu, Weijian Zhou
Atmospheric 14Co2 Observation: A Novel Method To Evaluate Carbon Emissions, Zhenchuan Niu, Peng Wang, Shugang Wu, Weijian Zhou
Bulletin of Chinese Academy of Sciences (Chinese Version)
As an important carbon emitter, China faces the stress of carbon peaking and carbon neutrality goals and international carbon reduction duty. The accurate data of carbon emissions are important to evaluate the carbon peaking and carbon neutrality goals and fulfill the international duty of carbon reduction. The Intergovernmental Panel on Climate Change (IPCC) report recommends the combination of top-down atmospheric CO2 observation with atmospheric inversion to verify the bottom-up inventory of carbon emissions, and the atmospheric 14CO2 observation can make the verification more accurate. Radiocarbon (14C) is the most precise tracer of fossil fuel CO2 and …
Spatial Agglomeration And Environmental Effects Of Heavy Polluting Industries In China: Characteristics And Enlightenment, Hongyang Chen, Jianhui Yu, Wenzhong Zhang
Spatial Agglomeration And Environmental Effects Of Heavy Polluting Industries In China: Characteristics And Enlightenment, Hongyang Chen, Jianhui Yu, Wenzhong Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
Heavy polluting industries are the important sources of industrial pollutant. Understanding the spatial agglomeration characteristics, influencing factors, agglomeration mechanism and environmental effects of China’s heavy polluting industries can help identify potential pollution risk areas to cope with increasingly severe environmental pollution problems. Based on the industrial economic data from 1999 to 2021, the spatial distribution and agglomeration characteristics of heavy polluting industries are characterized. It is found that: (1) Shandong, Jiangsu, Zhejiang, and Guangdong are the regions with high output value of the development of heavy polluting industries in the past 20 years, while Xinjiang, Inner Mongolia, Shanxi, Shaanxi, Henan, …
Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler
Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler
SMU Data Science Review
Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …
Occupational And Environmental Factors Influencing Morale Of United States Federal Wildland Firefighters, Rachel M. Granberg, Ting Shen, Seth W. Pearson, Robin M. Verble
Occupational And Environmental Factors Influencing Morale Of United States Federal Wildland Firefighters, Rachel M. Granberg, Ting Shen, Seth W. Pearson, Robin M. Verble
Psychological Science Faculty Research & Creative Works
Background. Wildland firefighters have physically and psychologically demanding jobs that can result in social, economic and health-related stress. Previous studies have examined the physiological and physical effects of a career in wildland fire, but fewer studies have addressed psychological effects, and to date, none have directly analyzed the hiring and work experiences of wildland firefighters. Aims. We surveyed work experiences, health and well-being, and morale of wildland firefighters, explored factors that can improve recruitment and retention, and summarized broad patterns. Methods. We conducted a voluntary anonymous survey of 708 federal wildland firefighters via an online platform over 2 months in …
Is The Declining Birthrate Really An Issue For The Economy?, Harsh Ramesh Pednekar, Theodore Lee, Darrion Chin
Is The Declining Birthrate Really An Issue For The Economy?, Harsh Ramesh Pednekar, Theodore Lee, Darrion Chin
Introduction to Research Methods RSCH 202
This study aims to explore the complex implications of declining birth rates on the economy, focusing on GDP per capita as a crucial metric, and aims to uncover both potential opportunities and challenges stemming from this demographic transformation using regression analysis. Using a quantitative methodology and secondary data from OECD.stat, World Population Review, and World Bank, the study explores the relationship between declining birth rates and economic impacts. GDP per capita serves as an essential dependent variable, and it accounts for control variables such as labour force participation, literacy, and education levels, child dependence ratio, and physical capital. Past studies …
Bitcoin And South African Stock Market Returns During Covid-19 Pandemic: A Test Of The Safe-Haven Hypothesis, Akaninyene U. Udom, Sopuru W. Nnamani
Bitcoin And South African Stock Market Returns During Covid-19 Pandemic: A Test Of The Safe-Haven Hypothesis, Akaninyene U. Udom, Sopuru W. Nnamani
CBN Journal of Applied Statistics (JAS)
This paper tests the safe-haven property of Bitcoin for South African stocks using Full and Diagonal BEKK-GARCH models. The study uses the Johannesburg stock exchange Top40 index, and bitcoin returns data before COVID-19 (August 2018 to December 2019) and during COVID-19 (January 2020 to June 2021). The results show that bitcoin cannot be considered as safe-haven for stocks in South Africa since it is weakly correlated with stock and had a high volatility during the Pandemic. Therefore, the safe-haven hypothesis of bitcoin on South African stocks is not true for the period under study. The policy implication is that bitcoin …
Generalized Ratio-Product Cum Regression Variance Estimator In Two-Phase Sampling, Isah Muhammad
Generalized Ratio-Product Cum Regression Variance Estimator In Two-Phase Sampling, Isah Muhammad
CBN Journal of Applied Statistics (JAS)
This study develops a flexible and efficient generalized ratio-product cum regression type estimator of population variance utilizing auxiliary variable in two-phase sampling that incorporates the properties of ratio-type and product-type estimators. The properties of the estimator were derived using first order approximation. The theoretical conditions under which the precision and the flexibility of the estimator is better than some classical estimators are also provided. Empirical evidence from five real datasets suggests that the proposed estimator outperforms the classical variance, ratio variance, product, and exponential ratio type estimators in terms of precision and efficiency. The estimator can be utilized to provide …
Modelling The Naira Exchange Rate Dependence Using Static And Time-Varying Copula, Kabir Katata
Modelling The Naira Exchange Rate Dependence Using Static And Time-Varying Copula, Kabir Katata
CBN Journal of Applied Statistics (JAS)
This paper examines the dependence structure of different currencies versus the Nigerian Naira using constant and time-varying copula. Daily Naira/USD, Naira/Yuan, Naira/Pound, and Naira/Euro exchange rates from 23 December 2011 to 12 May 2020 were utilised. We fitted eight constant and time-varying copula families using the exchange rate standardised residuals. The study finds that the Naira exchange rate may be estimated with student t-copula, Symmetrized Joe-Clayton (SJC), or Rotated Gumbel copula models and Autoregressive (AR)– Glosten Jagannathan RunkleGeneralized Autoregressive Conditional Heteroscedastic (GJR-GARCH) (1,1) models with skewed t residuals for margins. The Naira exchange rate returns is timevarying, tail-dependent, and asymmetric. …
External Debt Pass-Through To Inflation In Nigeria, Emmanuel A. Asue, James V. Ikyaator
External Debt Pass-Through To Inflation In Nigeria, Emmanuel A. Asue, James V. Ikyaator
CBN Journal of Applied Statistics (JAS)
This study examines external debt pass-through to inflation in Nigeria using annual data from 1981 to 2020 based on structural vector autoregressive (SVAR) model. The results reveal that an increase in external debt service leads to a significant depreciation of the exchange rate, which leads to a contemporaneous increase in inflation, while the direct response of inflation to external debt is statistically not significant. The impulse response confirms these results. The forecast error variance decomposition depicts that future values of official exchange rate depend on external debt, inflation and external debt service. The study recommends that the Nigerian government should …
Financial Inclusion And Poverty Reduction In Nigeria: The Role Of Microfinance Institutions, Okwudili W. Ugwuoke, Oliver E. Ogbonna, Aye-Agele Freeman
Financial Inclusion And Poverty Reduction In Nigeria: The Role Of Microfinance Institutions, Okwudili W. Ugwuoke, Oliver E. Ogbonna, Aye-Agele Freeman
CBN Journal of Applied Statistics (JAS)
This study investigates the role of microfinance institutions as a vehicle for driving financial inclusion and alleviating poverty in Nigeria using the EFinA 2018 household survey data. The probit model, propensity score matching, and average treatment effect methods are applied for the analyses. The study finds that financial inclusion driven by access to, and usage of products/services provided by microfinance institutions reduces poverty. The study recommends among others the need for increased access to microfinance products/services and an integrated poverty reduction policies that identifies microfinance institutions as a critical enabler
Editorial: The Public Health Scholars As The Health Leaders, Al Asyary, Meita Veruswati, Putri Bungsu Machmud, Indri Hapsari Susilowati
Editorial: The Public Health Scholars As The Health Leaders, Al Asyary, Meita Veruswati, Putri Bungsu Machmud, Indri Hapsari Susilowati
Kesmas
1. Achmadi UF. Kesehatan Masyarakat: Teori dan Aplikasi. Jakarta: Rajawali Pers; 2014.
2. Asyary A. Editorial. Kesmas. 2023; 18 (Special Issue 1): 1-3. DOI: 10.21109/kesmas.v18isp1.7201
3. Badan Kebijakan Pembangunan Kesehatan. Pembangunan Kesehatan di Indonesia melalui Kesinambungan Finansial Jaminan Kesehatan serta Meningkatkan Kualitas Layanan dengan Integrasi Data. Jakarta: Kementerian Kesehatan Republik Indonesia; 2023.
Mathematical Modeling Of The Impact Of Lobbying On Climate Policy, Andrew Jacoby, Claire Hannah, James Hutchinson, Jasmine Narehood, Aditi Ghosh, Padmanabhan Seshaiyer
Mathematical Modeling Of The Impact Of Lobbying On Climate Policy, Andrew Jacoby, Claire Hannah, James Hutchinson, Jasmine Narehood, Aditi Ghosh, Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
The Use Of Regularization To Detect Racial Inequities In Pay Equity Studies: An Empirical Study And Reflections On Regulation Methods, Christopher M. Peña
The Use Of Regularization To Detect Racial Inequities In Pay Equity Studies: An Empirical Study And Reflections On Regulation Methods, Christopher M. Peña
Electronic Theses and Dissertations
Since the late 1970s, multiple linear regression has been the preferred method for identifying discrimination in pay. An empirical study on this topic was conducted using quantitative critical methods. A literature review first examined conflicting views on using multiple linear regression in pay equity studies. The review found that multiple linear regression is used so prevalently in pay equity studies because the courts and practitioners have widely accepted it and because of its simplicity and ability to parse multiple sources of variance simultaneously. Commentaries in the literature cautioned about errors in model specification, the use of tainted variables, and the …
Does The Design And Personalization Of Mailed Invitations Influence Online Survey Response Rates?, Brock Ternes
Does The Design And Personalization Of Mailed Invitations Influence Online Survey Response Rates?, Brock Ternes
The SUNY Journal of the Scholarship of Engagement: JoSE
Nonresponse to online surveys has been a notable concern of survey methodologists, who continue to implement strategies and incentives to boost returns. Don Dillman’s methods emphasize tailored designs to maximize response rates, and this paper assesses how mailed notification designs and requested deadlines for completion influence online survey response rates. Using a target population of rural Kansans, this paper assesses how minor changes in printed notifications are connected to participation in an online survey. Postcards were mailed to private water well owners inviting recipients to complete a 40-item online questionnaire about their water usage; notifications varied in their personalization of …
Decentralized Science (Desci): A New Paradigm For Diverse And Sustainable Scientific Development, Feiyue Wang, Wenwen Ding
Decentralized Science (Desci): A New Paradigm For Diverse And Sustainable Scientific Development, Feiyue Wang, Wenwen Ding
Bulletin of Chinese Academy of Sciences (Chinese Version)
The rise of artificial intelligence for science (AI4S) has made it particularly important and urgent to ensure the openness, fairness, impartiality, diversity, and sustainability of scientific systems. This is significant to the discourse power and leadership of countries in global innovation and industrial revolution, and also affects the security, stability, and sustainable development of a community with a shared future for mankind. To address these challenges, AI4S needs to adopt new scientific organizational and operational methods. Decentralized science (DeSci) has emerged to vitalize AI4S and provide strong support, effectively addressing issues such as information silos, biases, unfair distribution, and monopolies …
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
I-GUIDE Forum
Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …
A Classical Fall Statistics Problem, Timothy Meyer
A Classical Fall Statistics Problem, Timothy Meyer
Cornhusker Economics
An evaluation of traditional baseball measures and suggestions for alternatives, centering on statistics related to the offensive quality of a player.
Academic Evaluation From The Perspective Of Multi-Source Eterogeneous Data:Connotation, Status And Prospect, Sanhong Deng, Jie Yang, Hao Wang, Jia Shen
Academic Evaluation From The Perspective Of Multi-Source Eterogeneous Data:Connotation, Status And Prospect, Sanhong Deng, Jie Yang, Hao Wang, Jia Shen
Journal of Scientific Information Research
[Purpose/significance]Academic evaluation and scientometric methods of synthesizing multisource heterogeneous data have gradually become hot spots in the field. At present, there is no systematic theoretical discussion on academic evaluation from the perspective of multisource heterogeneous data.[Method/process]In view of insufficient utilization of multi-source heterogeneous data, inappropriate research methods, and unclear research objectives, this paper combs the development of academic evaluation from the perspective of multi-source heterogeneous data, and clarifies the connotation and extension of the field, and analyzes the frontiers and hot spots in the field.[Result/conclusion]The results state clearly that from the perspective of multi-source heterogeneous data, academic evaluation manifests the …
The Prevalence Of Burnout In Saudi Arabia Dental Hygienists, Nouf Hamad Aldayel
The Prevalence Of Burnout In Saudi Arabia Dental Hygienists, Nouf Hamad Aldayel
Dental Hygiene Theses & Dissertations
Purpose: The purpose of this pilot study was to assess the prevalence of burnout in Saudi Arabian dental hygienists and identify risk factors associated with burnout. Methods: A descriptive survey design using the Copenhagen Burnout Inventory (CBI) assessed burnout among a convenience sample of n=123 Saudi dental hygienists. The survey was disseminated electronically to 1,000 Saudi Arabian dental hygienists. The CBI measures three subscales: personal, work-related, and client/patient-related burnout on a five-point Likert-type scale. The survey also included six demographic questions, two Likert-type, one “yes/no,” and one openended question, related to burnout. Descriptive statistics, one-way between subject’s ANOVA, independent samples …
A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes
A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes
Psychology Theses & Dissertations
There is a focus within the behavioral/social sciences on non-physical, psychological constructs (i.e., constructs). These constructs are indirectly measured using measurement instruments that consist of questions that capture the manifestations of these constructs. The indirect nature of measuring constructs results in a need of ensuring that measurement instruments are reliable. The most popular statistic used to estimate reliability is coefficient alpha as it is easy to compute and has properties that make it desirable to use. Coefficient alpha’s popularity has resulted in a wide breadth of research into its qualities. Notably, research about coefficient alpha’s distribution has led to developments …
Applying Structural Equation Modeling To Better Understand The Relationship Between Stressors, Social Support And Wellbeing In The Lives Of Spouse Dementia Caregivers, Craig Holden
Dissertations, Theses, and Capstone Projects
Applying Structural Equation Modeling to Better Understand the Relationship Between Stressors, Social Support and Wellbeing in the Lives of Spouse Dementia Caregivers considers the utility of Pearlin et al.’s (1990) stress process model in understanding the needs of spouse caregivers. Data were drawn from eight biennial waves of the University of Michigan Health and Retirement Study (HRS) and analyzed using structural equation modeling. The final study sample comprised 774 spouses, average age 73, who were categorized based on Alzheimer’s Disease and Related Dementia (ADRD) and non-ADRD caregiver status. Results showed that for the study sample as a whole, social support …
Making The Error Bar Overlap Myth A Reality: Comparative Confidence Intervals, Frank S. Corotto
Making The Error Bar Overlap Myth A Reality: Comparative Confidence Intervals, Frank S. Corotto
Georgia Journal of Science
Many interpret error bars to mean that if they do not overlap the difference is statistically “significant”. This overlap rule is really an overlap myth; the rule does not hold true for any conventional type of error bar. There are rules of thumb for estimating P values, but it would be better to show error bars for which the overlap rule holds true. Here I explain how to calculate comparative confidence intervals which, when plotted as error bars, let us judge significance based on overlap or separation. Others have published on these intervals (the mathematical basis goes back to John …
Using Geographic Information To Explore Player-Specific Movement And Its Effects On Play Success In The Nfl, Hayley Horn, Eric Laigaie, Alexander Lopez, Shravan Reddy
Using Geographic Information To Explore Player-Specific Movement And Its Effects On Play Success In The Nfl, Hayley Horn, Eric Laigaie, Alexander Lopez, Shravan Reddy
SMU Data Science Review
American Football is a billion-dollar industry in the United States. The analytical aspect of the sport is an ever-growing domain, with open-source competitions like the NFL Big Data Bowl accelerating this growth. With the amount of player movement during each play, tracking data can prove valuable in many areas of football analytics. While concussion detection, catch recognition, and completion percentage prediction are all existing use cases for this data, player-specific movement attributes, such as speed and agility, may be helpful in predicting play success. This research calculates player-specific speed and agility attributes from tracking data and supplements them with descriptive …
Indirect Aggression And Victimization: Investigating Instrument Psychometrics, Gender Differences, And Its Relationship To Social Information Processing, Taylor Steeves
Electronic Theses and Dissertations
The study of indirect bullying behaviors, relational aggression and social aggression, has been of theoretical importance and interest to researchers and psychologists within the last few decades. In this investigation, using a convenience sample of 451 late adolescents attending a private university in the mid-Atlantic U.S., I examined the factor structure of two measures of indirect bullying, the Young Adult Social Behavior Scale – Victim (YASB-V) and the Young Adult Social Behavior Scale – Perpetrator (YASB-P). Using confirmatory factor analysis (CFA), I found that the YASB-V comprised a four-factor model, differing from the model that had been identified in the …
Comparative Study Of Supervised Classification Techniques With A Modified Knn Algorithm, Noah Owusu
Comparative Study Of Supervised Classification Techniques With A Modified Knn Algorithm, Noah Owusu
Open Access Theses & Dissertations
The goal of classification is to develop a model that can be used to accurately assign new observations to labeled classes based on the patterns learned from the training data. K-nearest Neighbors algorithm (KNN) is a popular and widely used algorithm for classification, however, its performance can be adversely affected by the presence of outliers in a dataset. In this study we have modified this existing KNN algorithm that can alleviate the effect of outliers in a dataset, thereby improving the performance of the KNN algorithm. We compared the performances of the Modified KNN method and the Existing KNN algorithm …
Editorial, Al Asyary