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Full-Text Articles in Statistics and Probability

แนวทางการส่งเสริมการเรียนรู้ภาษาระยะแรกเริ่มสำหรับเด็กอนุบาล : การวิเคราะห์โมเดลสมการโครงสร้างพหุระดับ, ยุทธชัย ศิลาแลง Jan 2023

แนวทางการส่งเสริมการเรียนรู้ภาษาระยะแรกเริ่มสำหรับเด็กอนุบาล : การวิเคราะห์โมเดลสมการโครงสร้างพหุระดับ, ยุทธชัย ศิลาแลง

Chulalongkorn University Theses and Dissertations (Chula ETD)

การวิจัยครั้งนี้มีวัตถุประสงค์ดังนี้ 1) เพื่อวิเคราะห์และเปรียบเทียบการเรียนรู้ภาษาระยะแรกเริ่มสำหรับเด็กอนุบาลที่มีภูมิหลังแตกต่างกัน 2) เพื่อวิเคราะห์โมเดลสมการเชิงโครงสร้างพหุระดับปัจจัยที่ส่งผลต่อการเรียนรู้ภาษาระยะแรกเริ่มของเด็กอนุบาลและตรวจสอบความสอดคล้องข้อมูลเชิงประจักษ์ 3) เพื่อวิเคราะห์อิทธิพลของตัวแปรในระดับห้องเรียนที่มีผลต่อการเรียนรู้ภาษาระยะแรกเริ่มสำหรับเด็กอนุบาล 4) เพื่อเสนอแนะแนวทางการส่งเสริมการเรียนรู้ภาษาระยะแรกเริ่มของเด็กอนุบาลสำหรับผู้ปกครอง ครู ผู้บริหารและศึกษานิเทศก์ ตัวอย่างประกอบด้วยนักเรียนชั้นอนุบาลปีที่ 3 จำนวน 2864 คน และครูที่สอนนักเรียนระดับชั้นอนุบาลปีที่ 3 จำนวน 53 คน ซึ่งเก็บข้อมูลจากโรงเรียนจำนวน 35 แห่ง สังกัดสำนักงานเขตพื้นที่การศึกษาประถมศึกษากรุงเทพมหานคร สุ่มตัวอย่างโดยใช้วิธีการแบบหลายขั้นตอน (Multi-stage Random Sampling) เครื่องมือที่ใช้ในการวิจัยประกอบด้วยแบบบันทึกข้อมูลนักเรียน แบบสอบถามสำหรับครู การวิเคราะห์สถิติบรรยายด้วยโปรแกรม SPSS และการวิเคราะห์โมเดลสมการโครงสร้างพหุระดับ ด้วยโปรแกรม Mplus ผลการวิจัยพบว่า 1) เด็กอนุบาลที่มาจากครอบครัวที่มีภูมิหลังด้านเศรษฐานะต่างกันส่งผลต่อการเรียนรู้ภาษาระยะแรกเริ่มต่างกัน 2) โมเดลสมการเชิงโครงสร้างพหุระดับปัจจัยที่ส่งผลต่อการเรียนรู้ภาษาระยะแรกเริ่มของเด็กอนุบาลที่พัฒนาขึ้นมีความสอดคล้องกับข้อมูลเชิงประจักษ์ (χ2 = 258.664, p = .00, χ2/df = 2.694, CFI = 0.847, TLI = 0.751, RMSEA = .024, SRMRw= 0.242, SRMRb= 0.062) โดยระดับนักเรียนพบว่า สภาพแวดล้อมทางด้านภาษาที่บ้านมีอิทธิพลทางตรงเชิงลบและพัฒนาการของเด็กมีอิทธิพลเชิงบวกต่อการเรียนรู้ภาษาระยะแรกเริ่มของเด็กอนุบาล 3) ตัวแปรในระดับห้องเรียนที่มีผลต่อการเรียนรู้ภาษาระยะแรกเริ่มสำหรับเด็กอนุบาล พบว่า การจัดสภาพแวดล้อมทางภาษาในห้องเรียน และสมรรถนะการสอนภาษาของครูมีอิทธิพลทางตรงเชิงบวกอย่างมีนัยสำคัญทางสถิติ ตัวแปรทำนายทั้งหมดในระดับนักเรียนและระดับห้องเรียนสามารถอธิบายความแปรปรวนของการเรียนรู้ภาษาระยะแรกเริ่มสำหรับเด็กอนุบาลได้ร้อยละ 24 และ 95 ตามลำดับ 4) ผลการวิเคราะห์จากโมเดลการส่งเสริมการเรียนรู้ภาษาในห้องเรียนอนุบาล นำไปสู่ข้อเสนอแนะ 3 แนวทาง ดังนี้ (1) ผู้ปกครองไม่ควรเคร่งครัดด้านวิชาการที่บ้านกับเด็กมากเกินไปแต่ควรตระหนักถึงพัฒนาการที่สมวัยของเด็ก (2) ครูควรตระหนักถึงการจัดสภาพแวดล้อมในห้องเรียนให้มีความน่าสนใจด้วยการเปิดโอกาสให้มีประสบการณ์ทางภาษาที่หลากหลาย การอ่านหนังสือกับเด็กและการมีแหล่งทรัพยากรทางภาษาในห้องเรียน สำหรับตัวครูผู้สอนควรจะมีพื้นฐานด้านการสอนภาษาสำหรับเด็กอนุบาลและครูควรมีความถนัดและรักในการสอนภาษา (3) ผู้บริหารและต้นสังกัดควรกำหนดนโยบายส่งเสริม สนับสนุน และสร้างความเข้าใจให้ผู้ปกครอง ครู ผู้บริหารและศึกษานิเทศก์เข้าใจถึงการจัดการเรียนการสอนภาษาสำหรับเด็กปฐมวัยให้ตรงกัน


Local Or Import? A Compositional Analysis Of Aztec Ritual Ceramics In The Tuxtlas Frontier, Veracruz, Mexico, Matthew T. Meyer Jan 2023

Local Or Import? A Compositional Analysis Of Aztec Ritual Ceramics In The Tuxtlas Frontier, Veracruz, Mexico, Matthew T. Meyer

Murray State Theses and Dissertations

At the time of Spanish Contact in the early 16th Century the western Tuxtlas region formed part of the Aztec imperial frontier in the southern Gulf lowlands. The most apparent material manifestation of this imperial connection was Aztec-style Texcoco-Molded Censers, recovered primarily from sites that served local centralizing functions. While rare, these symbols may provide valuable information on the dynamics of frontier politics and the relations between this region and the distant core to which they were sending tax payments. Initial consideration of this adopted imperial style implies political linkages, but the mechanisms of introduction, knowledge transmission, imperial versus local …


Bayesian Structural Time Series Methods For Modeling Cattle Body Temperature In Heat-Stressed Animals, Lacey Quandt Jan 2023

Bayesian Structural Time Series Methods For Modeling Cattle Body Temperature In Heat-Stressed Animals, Lacey Quandt

Murray State Theses and Dissertations

Climate change has had devastating effects globally, most commonly talked about during natural disasters and rising temperatures. Notably, the climate concern is turning towards agriculture and livestock. With rising temperatures, the prolonged amount of heat stress put on animals, specifically cattle, is becoming more apparent. Heat stress has been linked to a reduction in cattle growing and fattening, feed intake, productivity, reproduction, and fertility; increased heart rates and respiration; changes in behavior; and mortality in severe cases. There are abatement strategies put in place to lower heat stress in cattle, such as improvements in shading and cooling, nutritional management, and …


Disciplines Different Of Fine-Grained Acknowledged Entity:A Case Of Doctoral Dissertations In Chinese Humanities And Social Sciences, Jiaxin He, Shijin Zhang, Jiayu Zheng, Xinlong Chu, Chengzhi Zhang Jan 2023

Disciplines Different Of Fine-Grained Acknowledged Entity:A Case Of Doctoral Dissertations In Chinese Humanities And Social Sciences, Jiaxin He, Shijin Zhang, Jiayu Zheng, Xinlong Chu, Chengzhi Zhang

Journal of Scientific Information Research

[Purpose/significance]Thesis acknowledgment is a public text in which the authors express their gratitude to individuals and institutions those support their research. It is helpful to understand the individuals and institutions that play a role in the cultivation of doctoral candidate in different disciplines by extracting the entities of acknowledgment and comparing the distribution of the objects of acknowledgment in the dissertations of different disciplines.[Method/process]In this paper, we gained more than 60 000 Chinese doctoral dissertations acknowledgment of 21 humanities and social sciences disciplines, extracted acknowledged entities from acknowledgment, and constructed a fine-grained classification system of acknowledgment entities. The classification system …


Assessing Spurious Correlations In Big Search Data, Jesse T. Richman, Ryan J. Roberts Jan 2023

Assessing Spurious Correlations In Big Search Data, Jesse T. Richman, Ryan J. Roberts

Political Science & Geography Faculty Publications

Big search data offers the opportunity to identify new and potentially real-time measures and predictors of important political, geographic, social, cultural, economic, and epidemiological phenomena, measures that might serve an important role as leading indicators in forecasts and nowcasts. However, it also presents vast new risks that scientists or the public will identify meaningless and totally spurious ‘relationships’ between variables. This study is the first to quantify that risk in the context of search data. We find that spurious correlations arise at exceptionally high frequencies among probability distributions examined for random variables based upon gamma (1, 1) and Gaussian random …


Comparison Of Policies Text On Information Technology Of China And The United States, Bolin Hua, Shihui Wu Jan 2023

Comparison Of Policies Text On Information Technology Of China And The United States, Bolin Hua, Shihui Wu

Journal of Scientific Information Research

[Purpose/significance]Information technology plays an important role in the comprehensive national power, whose development is closely associated with the government's guidance and support. It's under this background that China and the United States launched a series of policies to promote the development of information technology. Discovering the differences between China and the US's policies is of great significance for us to improve our strategic planning for future development.[Method/process]This study presents China and the US's most important policies on information technology in chronological order, and mines the policies' text via the co-word networks and the LDA model.[Result/conclusion]Reveal common concerns and different focuses …


การเปรียบเทียบการทำนายทิศทางของราคาหุ้นไทยโดยใช้ตัวแบบ Random Forests, Xgboost และ Lightgbm, สาธิตา ไชยมหา Jan 2023

การเปรียบเทียบการทำนายทิศทางของราคาหุ้นไทยโดยใช้ตัวแบบ Random Forests, Xgboost และ Lightgbm, สาธิตา ไชยมหา

Chulalongkorn University Theses and Dissertations (Chula ETD)

การศึกษานี้มีวัตถุประสงค์เพื่อทำนายทิศทางของหุ้นไทย โดยทำการทดลองเปรียบเทียบเครื่องมือทางสถิติด้วยตัวแบบ Random Forests, XGBoost และ LightGBM โดยใช้ตัวแปรค่าของข้อมูลก่อนหน้า (Lag Features) เพียงอย่างเดียว ข้อมูลตัวชี้วัด (Indicators) ของหุ้นเพียงอย่างเดียว และ ข้อมูลตัวชี้วัด (Indicators) ของหุ้นร่วมกับข้อมูลก่อนหน้า (Lag Features) กับทั้ง 3 ตัวแบบ ด้วยวิธีการปรับแต่งไฮเปอร์พารามิเตอร์ระหว่างการปรับให้เหมาะสมแบบเบย์ (Bayesian Search) และการค้นหาแบบสุ่ม (Random Search) ในการทำนายทิศทางหุ้นล่วงหน้า 1, 3, 5,10, 15, 30, 60, 90 และ 180 วัน โดยศึกษาหุ้นทั้งหมด 8 ตัวที่ต่างอุตสาหกรรม ดังนี้ เกษตรและอุตสาหกรรมอาหาร (AGRO) สินค้าอุปโภคบริโภค (CONSUMP) ธุรกิจการเงิน (FINCIAL) สินค้าอุตสาหกรรม (INDUS) อสังหาริมทรัพย์และก่อสร้าง (PROPCON) ทรัพยากร (RESOURC) บริการ (SERVICE) เทคโนโลยี (TECH) ข้อมูลราคาหุ้นจาก finance.yahoo.com ปี ค.ศ. 2014-2023 โดยเลือกหุ้นที่มีมูลค่าสูงสุดจากแต่ละกลุ่มอุตสาหกรรม ซึ่งขั้นตอนการแบ่งข้อมูลออกเป็นข้อมูลชุดฝึกฝน (Training Set) และข้อมูลชุดทดสอบ (Test Set) และทำการแบ่ง K-Fold Cross-Validation ทั้งหมด 5 Fold และวัดผลตัวแบบด้วยค่าความแม่นยำ (Accuracy), Precision, Recall, F1-Score และ AUC จากการศึกษาพบว่า ตัวแบบ Random Forests, XGBoost และ LightGBM มีผลลัพธ์การทำนายใกล้เคียงกันในแต่ละชุดตัวแปร และวิธีวิธีการปรับแต่งไฮเปอร์พารามิเตอร์ระหว่างการปรับให้เหมาะสมแบบเบย์ (Bayesian Search) และการค้นหาแบบสุ่ม (Random Search) ให้ผลลัพธ์ใกล้เคียงกันในแต่ละตัวแบบ …


Thai Language Sentiment Analysis With A Hybrid Method On Wangchanberta-Cnn-Bilstm, Kasidhit Suraratchai Jan 2023

Thai Language Sentiment Analysis With A Hybrid Method On Wangchanberta-Cnn-Bilstm, Kasidhit Suraratchai

Chulalongkorn University Theses and Dissertations (Chula ETD)

Understanding emotions conveyed in text, especially in non-global languages such as Thai, sentiment analysis is particularly important in Thailand. However, this endeavor faces challenges due to variations in text length, which significantly impact sentiment analysis outcomes. Previous research has employed neural network and machine learning models in the process from research [2] and [7], yet each model specializes in different aspects, making comprehensive sentiment analysis coverage unattainable. Recent research [13], has delved into hybrid models like CNN-BiLSTM and BiLSTM-CNN. Although they demonstrate efficacy, their performance still varies across different datasets. For instance, CNN-BiLSTM excels with short sentences by considering surrounding …


Identifying Potential Consequences Of Use Of A Measure Through Stakeholder Interviews, Melissa G. Kuhn, Joanna K. Garner, Shanan L. Chappell, Linda Bol Jan 2023

Identifying Potential Consequences Of Use Of A Measure Through Stakeholder Interviews, Melissa G. Kuhn, Joanna K. Garner, Shanan L. Chappell, Linda Bol

STEMPS Faculty Publications

The advent of Messick’s Contemporary Validity Theory (1994) led researchers in survey and measure design to develop and standardize qualitative and quantitative methods of collecting evidence for the validity of psychological instruments. However, one aspect of this theory, consequential validity, has few agreed-upon evidence-gathering methods (Furr & Bachrach, 2014). This study added a blueprint-driven interview method of collecting forecasted consequences of use of an instrument into the overall process of developing a measure of outreach impact on undergraduate engineering students (Authors, in press). The method, which included a purposeful sampling of end-users, is illustrated with thematically presented results. Potential implications …


Statistical Intervals For Neural Network And Its Relationship With Generalized Linear Model, Sheng Yuan Jan 2023

Statistical Intervals For Neural Network And Its Relationship With Generalized Linear Model, Sheng Yuan

Theses and Dissertations--Statistics

Neural networks have experienced widespread adoption and have become integral in cutting-edge domains like computer vision, natural language processing, and various contemporary fields. However, addressing the statistical aspects of neural networks has been a persistent challenge, with limited satisfactory results. In my research, I focused on exploring statistical intervals applied to neural networks, specifically confidence intervals and tolerance intervals. I employed variance estimation methods, such as direct estimation and resampling, to assess neural networks and their performance under outlier scenarios. Remarkably, when outliers were present, the resampling method with infinitesimal jackknife estimation yielded confidence intervals that closely aligned with nominal …


Probabilistic Methods For Inferring The Order Of Pathway Alterations During Carcinogenesis And Cancer Subtype Classification, Menghan Wang Jan 2023

Probabilistic Methods For Inferring The Order Of Pathway Alterations During Carcinogenesis And Cancer Subtype Classification, Menghan Wang

Theses and Dissertations--Statistics

Carcinogenesis is a complex process involving somatic mutations in a number of key biological pathways. Studying cancer evolution is an important task which contributes to better understanding of cancer biology and facilitates identification of new therapeutic targets. We focus on two important questions in cancer evolution. The first question is to delineating the temporal order of pathway mutations during tumorigenesis. And the other question is to cluster patients into biologically meaningful cancer subtypes. We present new statistical methods to 1)leverage functional annotations of mutations to enhance estimation of the order of pathway mutations during carcinogenesis, 2) incorporate intra-tumoral heterogeneity information …


Tolerance Intervals For Various Regression Models, Xitong Zhou Jan 2023

Tolerance Intervals For Various Regression Models, Xitong Zhou

Theses and Dissertations--Statistics

Among statistical intervals, confidence intervals and prediction intervals are well-known and commonly used. In many applications, the problem becomes finding an interval that covers at least a certain proportion $P$ of the population for a characteristic of interest with a specified confidence level $(1-\alpha)$. And such interval is named a $P$-content, $(1-\alpha)$-confidence Tolerance Interval (TI). The topic of the dissertation is the utility of tolerance intervals for various regression models. We begin with a discussion of tolerance intervals for linear and nonlinear regression models. We then propose a bootstrap method of constructing TIs for Tobit regression to deal with censored …


High Dimensional Data Analysis: Variable Screening And Inference, Lei Fang Jan 2023

High Dimensional Data Analysis: Variable Screening And Inference, Lei Fang

Theses and Dissertations--Statistics

This dissertation focuses on the problem of high dimensional data analysis, which arises in many fields including genomics, finance, and social sciences. In such settings, the number of features or variables is much larger than the number of observations, posing significant challenges to traditional statistical methods.

To address these challenges, this dissertation proposes novel methods for variable screening and inference. The first part of the dissertation focuses on variable screening, which aims to identify a subset of important variables that are strongly associated with the response variable. Specifically, we propose a robust nonparametric screening method to effectively select the predictors …


Novel Modelling And Inference Considerations Involving The Exponentially-Modified Gaussian Distribution, Yanxi Li Jan 2023

Novel Modelling And Inference Considerations Involving The Exponentially-Modified Gaussian Distribution, Yanxi Li

Theses and Dissertations--Statistics

The exponentially-modified Gaussian (EMG) distribution is well-suited for analyzing data with positive skewness due to its characteristic positive skew from the exponential component. Despite its popularity in various fields, the EMG distribution has only been analyzed for univariate data without any regression settings. To address this limitation, we developed a generalized EMG regression model with covariates by assigning parametric functional forms to some or all of the parameters in the EMG distribution that vary with values of the covariates. To further perform data-clustering on observation points, we propose a competing regression model where the error structure is assumed to be …


Finite Mixtures Of Mean-Parameterized Conway-Maxwell-Poisson Models, Dongying Zhan Jan 2023

Finite Mixtures Of Mean-Parameterized Conway-Maxwell-Poisson Models, Dongying Zhan

Theses and Dissertations--Statistics

For modeling count data, the Conway-Maxwell-Poisson (CMP) distribution is a popular generalization of the Poisson distribution due to its ability to characterize data over- or under-dispersion. While the classic parameterization of the CMP has been well-studied, its main drawback is that it is does not directly model the mean of the counts. This is mitigated by using a mean-parameterized version of the CMP distribution. In this work, we are concerned with the setting where count data may be comprised of subpopulations, each possibly having varying degrees of data dispersion. Thus, we propose a finite mixture of mean-parameterized CMP distributions. An …


Methodologies And Computational Tools For Zero-Inflated Discrete Weibull Models, Peng Yeh Jan 2023

Methodologies And Computational Tools For Zero-Inflated Discrete Weibull Models, Peng Yeh

Theses and Dissertations--Statistics

Count data with excess zeros is common in many fields, such as ecology, healthcare, and insurance. Excess zeros data are often causing the inaccurate fit from the count models. While zero-inflated models have been developing for over two decades, one should also consider a more flexible model that can handle the excess zeros and further over- or under-dispersion. In this talk, we discuss zero-inflated discrete Weibull model and some novel computational contributions. The flexibility and competitiveness of the ZIDW model are illustrated by simulation studies and a real data analysis. We also investigate the performance of the proposed model through …


Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky Jan 2023

Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky

Theses and Dissertations--Pharmacy

The introduction of antibiotics into clinical practice is considered the greatest medical breakthrough of the 20thcentury. However, the use of antibiotics can contribute to the development of resistance. In the United States (U.S.), approximately 2.8 million people are infected with antibiotic-resistant bacteria each year, and more than 35,000 people die as a result. Moreover, some antibiotics are known to cause cardiac side effects including QT prolongation, hypotension, and ventricular arrythmias. The U.S. Centers for Disease Control and Prevention (CDC) defines appropriate antibiotic use as the effort to use “the right antibiotic, at the right dose, for the right …


Clustering Hospital Performance Using Group-Based Multi-Trajectory Modeling With Singular Bayesian Information Criterion, Gaixin Du Jan 2023

Clustering Hospital Performance Using Group-Based Multi-Trajectory Modeling With Singular Bayesian Information Criterion, Gaixin Du

Theses and Dissertations--Epidemiology and Biostatistics

Hospital performance is complex and patient-experience oriented. Currently, the Centers for Medicare and Medicaid Services (CMS) evaluate hospitals yearly with a single score of one to five ("Star Rating") using composite measures from five domains. However, a single composite score cannot fully describe it, and alternative measures should be considered. Healthcare quality improvement needs long-term data to validate effectiveness. Group-based multi-trajectory modeling (GBMTM) estimates probabilities of latent group membership based on longitudinal profiles from multiple outcomes. We use GBMTM to identify groups of hospitals with similar performance in SAS PROC TRAJ.

We downloaded Medicare-eligible hospitals (N=5,111) that provided patient care …


Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp Jan 2023

Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp

Theses and Dissertations--Epidemiology and Biostatistics

In this series of studies, we examined the potential of a variety of blood-based plasma biomarkers for the identification of Alzheimer's disease (AD) progression and cognitive decline. With the end goal of studying these biomarkers via mixture modeling, we began with a literature review of the methodology. An examination of the biomarkers with demographics and other health factors found evidence of minimal risk of confounding along the causal pathway from biomarkers to cognitive performance. Further study examined the usefulness of linear combinations of biomarkers, achieved via partial least squares (PLS) analysis, as predictors of various cognitive assessment scores and clinical …


Economics Of Maple Syrup Production In Kentucky, Bobby Thapa Jan 2023

Economics Of Maple Syrup Production In Kentucky, Bobby Thapa

Theses and Dissertations--Forestry and Natural Resources

Maple syrup production is traditionally associated with New England regions in the United States, but there is growing interest in expanding it to other regions with suitable environmental conditions, including Kentucky. This study presents an in-depth analysis of the potential production and economic impacts of maple syrup in Kentucky using a multi-method approach. First, the study applies a stochastic production model to assess the effects of climatic and tree variables on maple syrup yield. The results reveal that several variables, including the number of maple trees, taps, temperatures, tapping season length, and time, significantly affect maple syrup yield. Second, input-output …


The Impact Of Subjective Risk Analysis On Real Estate Prices In The Nisqually Region Following The 2001 Nisqually Earthquake, Ryan Espedal Jan 2023

The Impact Of Subjective Risk Analysis On Real Estate Prices In The Nisqually Region Following The 2001 Nisqually Earthquake, Ryan Espedal

All Master's Theses

Earthquakes are an environmental hazard that pose great risks to communities almost every day. With earthquakes, the main cause of concern is physical destruction of property, however, there are also psychological effects that are researched and discussed much less. In 2001, the Nisqually area of western Washington experienced a substantial earthquake that produced minimal physical damage but caused a significant decrease in real estate prices. Studying single-family homes from 1986-2012, this research utilizes hedonic property models to measure the change in consumer’s subjective risk calculations with reference to real estate purchases after the Nisqually earthquake, measure the relationship between earthquake …


Beginner's Analysis Of Financial Stochastic Process Models, David Garcia Jan 2023

Beginner's Analysis Of Financial Stochastic Process Models, David Garcia

HMC Senior Theses

This thesis explores the use of geometric Brownian motion (GBM) as a financial model for predicting stock prices. The model is first introduced and its assumptions and limitations are discussed. Then, it is shown how to simulate GBM in order to predict stock price values. The performance of the GBM model is then evaluated in two different periods of time to determine whether it's accuracy has changed before and after March 23, 2020.


A Method For Quantifying Individual Decision Thresholds Of Latent Print Examiners, Amanda Luby Jan 2023

A Method For Quantifying Individual Decision Thresholds Of Latent Print Examiners, Amanda Luby

Mathematics & Statistics Faculty Works

In recent years, ‘black box’ studies in forensic science have emerged as the preferred way to provide information about the overall validity of forensic disciplines in practice. These studies provide aggregated error rates over many examiners and comparisons, but errors are not equally likely on all comparisons. Furthermore, inconclusive responses are common and vary across examiners and comparisons, but do not fit neatly into the error rate framework. This work introduces Item Response Theory (IRT) and variants for the forensic setting to account for these two issues. In the IRT framework, participant proficiency and item difficulty are estimated directly from …


An Exploration Of Parameter Duality In Statistical Inference, Suzanne Thornton, M. Xie Jan 2023

An Exploration Of Parameter Duality In Statistical Inference, Suzanne Thornton, M. Xie

Mathematics & Statistics Faculty Works

Well-known debates among statistical inferential paradigms emerge from conflicting views on the notion of probability. One dominant view understands probability as a representation of sampling variability; another prominent view understands probability as a measure of belief. The former generally describes model parameters as fixed values, in contrast to the latter. We propose that there are actually two versions of a parameter within both paradigms: a fixed unknown value that generated the data and a random version to describe the uncertainty in estimating the unknown value. An inferential approach based on CDs deciphers seemingly conflicting perspectives on parameters and probabilities.


The Chains That Bind: Gender, Disability, Race, And It Accommodations, Eleanor T. Loiacono, Shiya Cao Jan 2023

The Chains That Bind: Gender, Disability, Race, And It Accommodations, Eleanor T. Loiacono, Shiya Cao

Statistical and Data Sciences: Faculty Books

This chapter explores intersectionality of gender, disability, and race relevant to Information Technology (IT) accommodations and employment. More specifically, we investigate individuals’ experiences and differences in receiving IT accommodations as an organizational diversity intervention that helps disabled employees integrate into the workplace. The goal of this chapter is to seek a better understanding of individual differences in the accommodation process and how to empower disabled women in the workplace. To do so, by applying the Individual Differences Theory of Gender and IT (IDTGIT), we focus on the experiences disabled men and women have with regard to IT accommodations as well …


System For Scanning And Monitoring Science And Technology Policy Texts Of Us And Eu, Dahai Yu, Aofei Chang, Bolin Hua, Hongguang Wang, Wenjiao Zheng Jan 2023

System For Scanning And Monitoring Science And Technology Policy Texts Of Us And Eu, Dahai Yu, Aofei Chang, Bolin Hua, Hongguang Wang, Wenjiao Zheng

Journal of Scientific Information Research

[Purpose/significance]Science and technology policy plays a guiding role in the development of science and technology. Whether science and technology policies are efficient and reasonable has an important impact on the rapid development of science and technology. In order to help decision-makers grasp the latest international scientific and technological layout, planning and policy guidance more quickly, especially to track and analyze the scientific, and technological policies of major developed countries in Europe and the United States, grab analyze and mine the corresponding scientific and technological policy texts in real time, has of great significance in the current international environment.[Method/process]This research designed …


Odd Solutions To Systems Of Inequalities Coming From Regular Chain Groups, Daniel Slilaty Jan 2023

Odd Solutions To Systems Of Inequalities Coming From Regular Chain Groups, Daniel Slilaty

Mathematics and Statistics Faculty Publications

Hoffman’s theorem on feasible circulations and Ghouila-Houry’s theorem on feasible tensions are classical results of graph theory. Camion generalized these results to systems of inequalities over regular chain groups. An analogue of Camion’s result is proved in which solutions can be forced to be odd valued. The obtained result also generalizes the results of Pretzel and Youngs as well as Slilaty. It is also shown how Ghouila-Houry’s result can be used to give a new proof of the graph- coloring theorem of Minty and Vitaver.


Carnivore And Ungulate Occurrence In A Fire-Prone Region, Sara J. Moriarty-Graves Jan 2023

Carnivore And Ungulate Occurrence In A Fire-Prone Region, Sara J. Moriarty-Graves

Cal Poly Humboldt theses and projects

Increasing fire size and severity in the western United States causes changes to ecosystems, species’ habitat use, and interspecific interactions. Wide-ranging carnivore and ungulate mammalian species and their interactions may be influenced by an increase in fire activity in northern California. Depending on the fire characteristics, ungulates may benefit from burned habitat due to an increase in forage availability, while carnivore species may be differentially impacted, but ultimately driven by bottom-up processes from a shift in prey availability. I used a three-step approach to estimate the single-species occupancy of four large mammal species: mountain lion (Puma concolor), coyote …


Eeg-Based Spanish Language Proficiency Classification: An Eeg Power Spectrum And Cross-Spectrum Analysis, Blaise Xavier O'Mara, Skyler Baumer Jan 2023

Eeg-Based Spanish Language Proficiency Classification: An Eeg Power Spectrum And Cross-Spectrum Analysis, Blaise Xavier O'Mara, Skyler Baumer

Honors Theses and Capstones

Second language proficiency may be predicted with electrophysiological techniques. In a machine learning application, this electrophysiological data may be used for language instructors and language students to assess their language learning. This study identifies how electroencephalogram (EEG) power spectrum and cross spectrum data of the brain cortex relates to Spanish second language (L2) proficiency of 20 Spanish language students of varying proficiency levels at the University of New Hampshire. The two metrics for assessing cortical power and processing were event-related desynchronization (ERD)—a measure of relative change in power—of the alpha (8-12 Hz) brain frequency band, and alpha and beta (13-30Hz) …


Occurrence Of Per- And Polyfluoroalkyl Substances (Pfas) In New Hampshire Biosolids, Katherine A. Wieck Jan 2023

Occurrence Of Per- And Polyfluoroalkyl Substances (Pfas) In New Hampshire Biosolids, Katherine A. Wieck

Honors Theses and Capstones

Per- and polyfluoroalkyl substances (PFAS) are a group of over 4,000 compounds used in the manufacturing of products including aqueous film forming foams for firefighting, stain repellents, waterproofing agents, and nonstick cookware since their initial development in the 1940s. The long fluorinated carbon chain structure of PFAS causes chemical and thermal stability, and thus resistance to biodegradation. Biosolids produced at wastewater facilities for uses such as agricultural land-applied compost and fertilizer for lawns and athletic fields, as well as sludge disposed in landfills can cause contamination of groundwater and surface water. This poses a significant threat to human and environmental …