Nonparametric Statistical Techniques Research Articles

Peningkatan Kemampuan Berfikir Kritis dan Pemecahan Masalah Matematis Siswa antara Siswa yang Diberi Pelajaran Kooperatif Tipe TPS Square dan TPS Share

This study aimed to assess the difference in improving critical thinking and mathematical problem-solving abilities among students receiving cooperative learning with the TPS Square and TPS Share methods. The experimental method utilized a pretest-posttest control group design involving two groups of students from a secondary school. One group received instruction using the TPS Square method, while the other group utilized the TPS Share method. Research instruments comprised tests on critical thinking and mathematical problem-solving abilities. Data collected were analyzed using non-parametric statistical techniques. The results of the analysis revealed a significant improvement from the pretest to the posttest, as reflected in higher test scores in the final stage. Based on the t-test calculations, the critical value (t-table) at a significance level of 5% (α = 0.05) was found to be 2.514. With the computed t-value exceeding the critical value (2.157 > 2.514), it can be concluded that there is a significant difference in the average critical thinking and mathematical problem-solving abilities before and after instruction using the cooperative learning models TPS and TPSq among the students of grade XII at SMA Al Washliyah 1 Medan during the academic year 2022-2023.

Effectiveness of the implementation of educational programs on healthy nutrition, implemented within the framework of the Demography national project

Introduction. Within the Demography National Project, the Federal Service for Supervision in Protection of the Rights of Consumer and Man Wellbeing (Rospotrebnadzor) performs specific activities aimed at creating an environment that raises people’s awareness about health diets. The number of people who have been educated on the matter represented an index of the key performance, unfortunately, it does not show whether any socially significant results have been achieved, first of all, concerning health protection. The aim of this study is to suggest a complex approach to assessing effectiveness of introduction of educational programs on health diets implemented within the Demography National Project. Materials and methods. Effectiveness of educational activities was assessed using the data obtained following the introduction of The Educational Program for Population Residing in Specific Areas as regards Environmental Exposures (macro- and micro-nutrient deficiency, specific climatic conditions) (hereinafter called The Program). The program was implemented relying on an educational resource for distance learning between April 2021 and May 2024. The obtained data was analyzed by using non-parametric statistical techniques. Health status was analyzed using data on incidence associated with unhealthy diets. Economic efficiency was estimated in conformity with the established methodology. Results. A complex approach is suggested to assess whether implementation of educational programs is effective. It includes such characteristics as a number of people, who mastered a program; level of attained knowledge and its trend; modelling a relationship that involves determining how many disease cases have been prevented; as well as economic efficiency assessment. Using one Program as an example, we analyzed such indices as the percentage of population who mastered it; their initial and attained level of knowledge (according to data obtained by control activities); the percentage of people with positive trend in the level of attained knowledge (per the results of individual check-ups). In addition to that, we calculated the number of prevented diseases associated with unhealthy diets (four hundred seventy two diseases of the musculoskeletal system) with the following assessment of implemented activities per economic indices (not less than 41.5 million rubles of the gross domestic product (GDP) losses prevented annually). Limitations. When analyzing how many people mastered the program, we relied on data about introduction of the program based on using only one communication channel. Conclusion. Use of this complex approach to assessing effectiveness of implementation of educational programs on healthy diets makes it possible to clearly show whether short-term goals (percentages of people with positive trend in the level of attained knowledge are the most informative index) as well as long-term ones (incidence associated with unhealthy diets) have been successfully achieved. It also allows estimating economic efficiency of implemented activities.

Determination of 99th percentile upper reference limit of cardiac troponin I in healthy population of Rahim Yar Khan.

Objective: To determine the 99th percentile upper reference limit (URL) of cardiac troponin I (cTnI) in healthy population of Rahim Yar Khan. Study Design: Cross-sectional study. Setting: Department of Chemical Pathology, Sheikh Zayed Hospital, Rahim Yar Khan. Period: February 2023 to November 2023. Methods: A total of 262 healthy individuals aged between 20-76 years without any known cardiac diseases were included and selection was performed on the basis of a designed questionnaire. Serum hs-cTnI was measured using a chemiluminescent technique on ACCESS II, Beckman Coulter. A non-parametric statistical technique was used to establish the 99th percentile upper reference limit (URL) of hs-cTnI in accordance with CLSI Document C28-A3c. Mann Whitney U test was applied between two subgroups taking p value <0.05 as significant. Results: In this study, 136 (51.9%) were males and 126 (48.1%) were females. Of the total 262 study subjects, 180(68.7%) had values greater than Limit of detection (LoD) 2.3 ng/L while 82(31.3%) had values less than LOD. Overall, Male and Female 99th percentile URL of hs-cTnI in population of Rahim Yar Khan was found to be 10.8, 13.1 and 8.3 ng/ml respectively before removing any outliers. After removing outliers by Dixon/Reed method, the 99th percentile URL found to be 8.4, 9.0 and 6.3 ng/L for overall, males and females respectively. The distribution troponin I with respect to age and gender was statistically significant with p value <0.05. Conclusion: On the basis of our study, it was concluded that the study population's overall high-sensitive cardiac troponin I 99th percentile URL was found to be significantly lower than both manufacturer-quoted values and results published in prior publications. High-sensitive troponin assay allows precise quantification of very low cardiac troponin concentration that helps in rapid exclusion of myocardial infarction.

Analysis of the survival of agricultural exporting firms in Peru, 2009-2019

Background At the international level, the survival of exporting companies represents a critical issue in a context of heightened uncertainty and intensified competition within the framework of the country’s commercial opening. This is a context in which different companies are born and die as a result of the interaction between the market and other factors. The objective of this research was to analysis of the survival of exporting agricultural companies in Peru, 2009-2019. To this end, data from the Commission for the Promotion of Peru for Exports and Tourism (Promperu) was utilised. Methods The methodological contribution of the research is based on the quantitative approach, of basic type with a descriptive elk; being the population that involves a total of data of the agricultural exporting companies of Peru in the period 2009-2019 and the sample is census and the non-parametric statistical technique used was the Kaplan Meier estimate for the estimation of the survival rate. Results Exports of Peru’s non-traditional agricultural sector in FOB value have had an average annual growth of 12% in terms of FOB value and 9% in terms of volume exported; the entry rate of new agro-exporting agricultural companies reached an average growth of 2.3% and the exit rate reached an average of 2.2% in the period 2009-2019. Conclusions The survival of exporting companies in the non-traditional agricultural sector is critical, where 89% of them survive only one year, while in the second year only 75% survive and in the sixth year only 33% survive.

The challenge of dissecting the frog: cartoonists analyze their creative process

Abstract This article delves into two intrinsic tensions present in humor and cartoons: funniness-seriousness and repetition-novelty. The focus is on the perspectives of cartoonists regarding the semiotic and rhetorical resources they put into play to create humor and satire. In this way, the study echoes a key question in semiotics, and particularly in multimodal studies: how image and words interplay in meaning-making. With that aim, a questionnaire was designed and filled out by 100 cartoonists from 22 different countries. The responses were analyzed applying mixed methods (content analysis, non-parametric statistical techniques, and network analysis). Based on the findings, four distinct profiles of cartoonists were identified, ranging from those who prioritize multimodality (the largest group) to those who favor the verbal mode. Cartoonists who prioritize the visual mode and skeptics to humor analysis fall in between. The article also discusses the various rhetorical resources that cartoonists declare to use to create humor, with irony and sarcasm being the most frequent ones, while puns are the least common. The results are examined in relation to the cartoonists’ conceptions of humor, satire, and the cartoon genre, as well as the different dimensions they considered when discussing their humor style. The study contributes to gaining a deeper understanding of the ways cartoonists use image and writing to create humor and satire and sheds light on an under-researched area in this field.

Compliance with MAB-UNESCO Functions and Management Effectiveness Evaluation between 2017 and 2024: Case Study of the El Cielo Biosphere Reserve, Mexico’s Only State-Run Reserve Belonging to MAB-UNESCO

UNESCO’s MAB Programme promotes a people-centered conservation strategy to strengthen the sustainability of social and ecological systems. However, there exist knowledge gaps regarding its implementation in specific contexts. For this study, a mixed-methods sequential exploratory design was employed. In the first phase, an initial content analysis of the management program of the El Cielo Biosphere Reserve (CBR) and the functions of the statutory framework of UNESCO’s MAB program was conducted. This analysis, which was human-driven but facilitated by artificial intelligence tools, underwent rigorous triangulation and expert validation to strengthen the reliability and robustness of the findings. Subsequently, the Management Effectiveness Tracking Tool (METT3) was issued to researchers, community members, civil servants, and former civil servants related to the management of the CBR. The 2024 results (n = 15) were contrasted with those obtained in 2017 (n = 15) using a quantitative approach consisting of descriptive, non-parametric, and Bayesian statistical techniques. We identified some problems in the implementation of the MAB-UNESCO Programme in the CBR, mainly due to the outdated management program and lack of effective governance, as well as the lack of understanding of the implications of being a MAB-UNESCO biosphere reserve. A numerical trend of deterioration in the effectiveness of the CBR’s management was detected, with overall ratings of 44.78% and 29.62% in 2017 and 2024, respectively. This was associated with a lack of regulation, weak coordination among key actors, and a progressive reduction in funding. The findings of this study are useful to guide the transition of the CBR towards a conservation model that responds to current problems and contributes to the advancement of knowledge on the implementation of the MAB Programme in specific contexts.

Malignant thyroid lump multi classification by TIRADS using DBA with transfer learning

Thyroid diseases have developed into significant illnesses in recent decades. These diseases affect the thyroid glands and are caused by elevated thyroid hormone levels or infections in the thyroid organs. It is challenging to resolve thyroid diagnosis using conventional parametric and nonparametric statistical techniques since it can be viewed as a classification problem. However, there are certain barriers in the manner of obtaining both efficacy and accuracy in thyroid nodule diagnosis. Deep learning (DL) and machine learning (ML) models have emerged as useful instruments for the diagnosis of sickness in the modern era. For the purpose of diagnosing and classifying thyroid diseases, this research introduces a novel deep belief network (DBF) with transfer learning, known as DBNTL. In this study, the pre-processed image was first pre-processed using a conventional multiresolution bilateral technique, and then it was subjected to a novel segmentation technique called fusion pooling integrated U-net segmentation. The DBN with transfer learning model is used to classify and grade malignant thyroid nodules in compliance with thyroid imaging-reporting-and-data-system (TIRADS) guidelines. In this model, the model's weights are obtained by transfer learning. A major metric for evaluating the efficacy of biological image processing applications, good sensitivity and specificity (97.28 and 97.22, respectively) were obtained for the recommended modes.

Functional clustering of NPLs recovery curves

Functional clustering of NPLs recovery curves

Reducing costs and improving patient recovery through a nurse-driven centralized spinal orthoses program on a post-surgical unit: A quality improvement initiative

An external vendor providing off-the-shelf spinal orthoses to inpatients created significant costs and barriers to quality care for spinal surgery patients. A nursing leadership team initiated a quality improvement project to reduce the cost of providing off-the-shelf spinal orthoses and improve the care provided to spinal patients. To develop and evaluate a nursing-led process for providing off-the-shelf orthoses to spinal surgery patients and eliminate high costs. Quality improvement project evaluated as a retrospective interrupted time-series. Post Surgery Inpatient Unit Level II Trauma Center in a United States hospital located in Florida. Vendor Program: 134 patients; Centralized Program: 155 patients. The nursing leadership team developed a centralized spinal orthoses program where the bedside nurse fitted the patient with a spinal orthosis, eliminating the need for an external orthotist. The study quantifies changes in study metrics by comparing patients identified through chart review who received care in the vendor program to those who received care in the centralized program utilizing nonparametric statistical techniques. The centralized nursing-led spinal orthosis program allowed the unit to mobilize patients more quickly than patients managed under the vendor program (3.85 hr. [95 % CI: 1.27 to 7.26 hrs] reduction; p = 0.004). The overall length of stay was reduced by 0.78 days ([1.34 - 0.02 days]; p = 0.063) or 18.72 h. While the statistical test did not indicate significance, the 18.72-hour reduction in length of stay represents a potential clinically relevant finding. Evaluating patients that suffered a primary spinal injury and no complications (vendor program: 54 patients; centralized program: 86 patients) showed a similar reduction in time to mobilization (4.5 hr reduction [0.53 to 12.93 hrs]; p = 0.025), but the length of stay reduction increased to 1.02 days [0.12 to 1.97 days], a difference determined to be statistically significant (p = 0.014). Centralizing the process for providing off-the-shelf spinal orthoses reduced the cost of a thoracic-lumbar sacral orthosis by $1,483 and the price of a lumbar-sacral orthosis by $1,327. Throughout the study, the new program reduced the cost of providing spinal orthoses by $175,319. The results demonstrate that the nursing-led centralized spinal orthosis program positively impacted the quality of care provided to our patients while also reducing the cost of delivering the orthoses. A nursing-led centralized spinal orthosis program reduces the cost of care while reducing time to mobilization and length of stay.

Remote sensing-based estimation of precipitation data (2000-2015) in Ecuador's Loja province

The primary climatic parameter frequently scrutinized in water balance assessments for water utilization is precipitation. Given its considerable variability across locations and over time, it is imperative to rely on high-quality statistical information to facilitate accurate analyses. This study aims to refine the estimation of precipitation data by enhancing information obtained from freely accessible satellite sensors with data collected from established observation stations. Monthly precipitation data spanning from 2000 to 2015 were gathered from 24 stations. Three distinct methodologies were employed to adjust individual station data to address missing data. Consistency analysis and data refinement were conducted for stations requiring adjustments, utilizing graphical analysis and non-parametric statistical techniques. The satellite products under evaluation correspond to the IMERG v6 algorithm. Subsequently, statistical metrics were used to compare observed and estimated data. A correction coefficient was computed by aligning monthly means between observed and calculated data to mitigate random and systemic errors. The IMERG algorithm demonstrates proficiency in accounting for altitude and seasonal variations, with the adjustment significantly enhancing its performance under these conditions.

Evaluating rail transit assignment models in the temporal dimension: The problem and its solution

Evaluating rail transit assignment models in the temporal dimension: The problem and its solution

A Consumer Data Privacy Protection Model Based on Non-Parametric Statistics for Dynamic Data Publishing in e-Commerce Platforms

Objectives: Consumer data privacy on e-commerce platforms is increasingly crucial. This study aims to investigate privacy protection mechanisms, particularly focusing on personal and corporate secrets. It seeks to understand individual perspectives on privacy and preferences for data disclosure. The primary objective is to explore methods for safeguarding personal information while maintaining data integrity. Methods/Analysis: We employ non-parametric statistical techniques to analyze consumer behavior and preferences on e-commerce platforms. This involves examining patterns of data disclosure and identifying sensitive information shared by users. By studying communication dynamics and recording practices, we assess the efficacy of current privacy protection measures. Novelty/Improvement: This study contributes to the understanding of consumer privacy protection by emphasizing the importance of non-parametric statistical methods in e-commerce research. Our findings underscore the need for enhanced privacy measures. We advocate for further research and development of innovative privacy-enhancing technologies to address evolving privacy challenges in online commerce. Findings:Our research highlights the significance of personal privacy concerns in e-commerce settings. We identify a spectrum of privacy attitudes among users, ranging from strict confidentiality to selective disclosure. Furthermore, our analysis reveals potential vulnerabilities in current privacy safeguards, particularly regarding the collection and storage of sensitive data on e-commerce platforms. Doi: 10.28991/HIJ-2024-05-02-013 Full Text: PDF

On Some Factors Contributing to Entrepreneurial Economic Success in South-West, Nigeria: An Empirical Approach

This essay explores the elements that lead to the financial success of entrepreneurs. In particular, it conducted an empirical investigation into the possibility that factors such as age, religious beliefs, risk-taking, marketing strategies, timely and adequate planning, employees’ commitment, accessibility to working capital, reduced bureaucratic steps on import and export matters, education level, and age and technology infrastructure could influence an entrepreneur’s level of success. The study used a descriptive survey research design. The study’s participants were business owners in the six states that make up Nigeria’s southwest region who operated on a micro, small, and medium scale. The 720 entrepreneurs who made up the study’s sample were chosen through a multi-stage sampling process. A self-structured questionnaire covering all the objectives was used as the data collection tool, and it was administered to a select group of entrepreneurs. In addition to applying non-parametric statistical techniques like the chi-squared test and phi statistic, the collected data were analyzed using descriptive statistics like frequencies, percentages, and graphics. In the R-Studio (Posit) environment, the data analysis operations were carried out. The findings showed that a successful entrepreneurship is greatly influenced by a number of factors, including the availability of operating capital, the degree of employee commitment, technological and infrastructural capabilities, risk-taking, effective marketing strategies, adequate and appropriate planning, educational attainment, and age. Success in entrepreneurship, however, is unrelated to fewer bureaucratic procedures involved in the import and export of goods. It was determined that the bulk of the previously mentioned elements affect any business’s ability to succeed in today’s world. Thus, it was suggested that all tiers of government be counselled to provide funding, among other things, to serious business owners.

Spatial and Temporal Analysis of Road Traffic Accidents in Major Californian Cities Using a Geographic Information System

Road traffic accidents have increased globally, which has led to significant challenges to urban safety and public health. This concerning trend is also evident in California, where major cities have seen a rise in accidents. This research conducts a spatio-temporal analysis of traffic accidents across the four major Californian cities—Los Angeles, Sacramento, San Diego, and San Jose—over five years. It achieves this through an integration of Geographic Information System (GIS) functionalities (space–time cube analysis) with non-parametric statistical and spatial techniques (DBSCAN, KDE, and the Getis-Ord Gi* method). Our findings from the temporal analysis showed that the most accidents occurred in Los Angeles over five years, while San Diego and San Jose had the least occurrences. The severity maps showed that the majority of accidents in all cities were level 2. Moreover, spatio-temporal dynamics, captured via the space–time cube analysis, visualized significant accident hotspot locations. The clustering of accidents using DBSCAN verified the temporal and hotspot analysis results by showing areas with high accident rates and different clustering patterns. Additionally, integrating KDE with the population density and the Getis-Ord Gi* method explained the relationship between high-density regions and accident occurrences. The utilization of GIS-based analytical techniques in this study shows the complex interplay between accident occurrences, severity, and demographic factors. The insight gained from this study can be further used to implement effective data-driven road safety strategies.

Career Guidance Based on Krumboltz's Social Learning Theory to Develop Students' Career Decisions

Career decisions impact an individual's success and satisfaction in their career. Various factors can hinder teenagers' career decision-making, affecting their future career paths. This research aims to produce career guidance based on Krumboltz's social learning theory that is effective for developing students' career decisions. This research is quantitative research using a positivism paradigm with a quasi-experimental design experimental method. Participants in this research involved 493 people, namely class XI high school students, guidance and counseling expert lecturers, and high school guidance and counseling teachers. Sample selection was carried out using a purposive sampling technique taken based on the class with the lowest score through data collection using an instrument in the form of a career decision questionnaire that had been developed and tested rationally. The data analysis technique used is inferential statistics with the non-parametric statistical testing technique Mann Whitney u test. The research results show a sign value (2-tailed) of 0.008<0.05, which means that career guidance based on Krumboltz's social learning theory is effective for developing students' career decisions. It can be concluded that career guidance based on Krumboltz's social learning theory to develop students' career decisions can be used in career guidance in high school. The principles of Krumboltz's theory in a context that has never been explored before, provide a new perspective that shows novelty in the career guidance approach. This research implies that Guidance and Counseling teachers can apply Krumboltz's social learning theory in career guidance to assist students in making career decisions.

Integrating industry-crowdsourced projects in university capstone courses: A comparative study using parametric statistics and sentiment analysis

This study explores integrating industry-crowdsourced projects within capstone courses of a 4-year Bachelor of Science program at an accredited American university. A unique business consulting model was developed for the final year course, aligning students with 16-weeks industry projects that reflected their academic goals and the program’s learning objectives. The study aimed to evaluate the efficacy of this pedagogical approach compared to traditional capstone courses. This evaluation involved collecting data from grading systems and anonymous course surveys. A novel aspect of the research design was the synergetic combination of nonparametric and parametric statistical techniques with modern machine learning (ML) algorithms to analyse the students’ grades, survey comments and third-party course opinion comments. Additionally, independent third-party course ratings were examined to triangulate the results. Findings revealed that while the academic performance in the industry-crowdsourced capstone course mirrored that of the traditional course, the industry-crowdsourced variant elicited significantly more positive responses in course surveys. Furthermore, ML sentiment analysis of comments from third-party forums indicated a stronger positive reception for the industry-crowdsourced course over the traditional approach.

Module Discovery Learning Biodiversity Material Based on Gunungkidul Beach to Increasing Interest and Independence in Learning of High School Students

The research carried out aims to determine the feasibility, practicality and effectiveness of the Gunung Kidul beach-based Discovery Learning module, on biodiversity material in increasing high school students' interest and independence in learning. The research carried out is a type of development research using the ADDIE model which consists of several stages, namely analysis, design, development, implementation and evaluation. The product produced in this research is a biology learning module on biodiversity material which is integrated with the Gunung Kidul beach-based Discovery Learning learning model. The learning module developed was validated by expert validators and practitioners, then tested for effectiveness on class X students of SMA N 1 Depok Sleman using the non-equivalent pre-test, post-test control group design technique. Data collection was carried out using direct interview techniques with biology teachers and distribution of student needs analysis questionnaires, assessment of material experts, media experts, learning experts, teacher and student practicality, student learning interest questionnaires, and student learning independence questionnaires. Data analysis uses non-parametric statistical test techniques with the Mann-Withney model, parametric statistical tests with the independent sample t test model and N-gain score. Gunung Kidul beach-based discovery learning learning modules on biodiversity material are feasible, and can be practically used in learning activities and are effectively used in increasing high school students' interest and independence in learning

Emotion Regulatory from Riding Aggressively on Motor Bike Students

Aggressive driving is aggressive behaviour carried out by drivers that can harm other drivers and themselves. Aggressive driving can be a contributing factor to increased accidents and traffic violations. One factor that can influence aggressive driving is emotional regulation. The study aimed to analyze the impact of emotional regulation on driving aggressiveness in motorcycle students. The study used an emotional regulation scale and a driving aggressiveness scale. Respondents in this study of male students in the city of Makassar were as many as 123, obtained using convenience sampling. This research uses a quantitative approach with nonparametric statistical data analysis techniques of ordinal regression methods. The results of this study show that there is a negative and significant influence of emotional regulation on driving aggression in male students in Makassar City (B = -0,063, p = 0,008), with 4.6% of driving aggressiveness contributing to the explanation of emotion regulation variance (R2 = 0,046). The higher the driver's ability to regulate emotions, the lower the motorcyclist's driving aggressiveness, and the worse the rider's emotion regulation ability, the higher the motorcycle rider's driving aggression. This research could be the basis for intervention or emotional regulation training in drivers in order to improve their ability to regulate emotions, thereby reducing levels of aggression while driving.

Organizational Commitment: The Key to Reduce Employees’ Resistance to Change

This report recognizes some of the most important causes of resistance to organizational change; some of which are related to the skills of employees and others to the company's communication procedures, which affects the work performance of employees and the image of the organization. To achieve the organization's objectives, the importance of structural change management, organizational culture, and the ability to modify strategies when circumstances warrant is also documented: First to contain, and then to reduce resistance to organizational change. The report includes a comparison of the proportion of successful and unsuccessful efforts regarding resistance to "organizational change"; a process that can be conceived as a "dialectical progression", whose main support is the institutional commitment implicit in the mission, vision, and core values of the organization. A nonparametric statistical technique: Jonckheere-Terpstra test was selected to perform the data analysis.

Covid-19 Dan Dampaknya Pada Kinerja Keuangan Perusahaan Manufaktur Di Indonesia

At the end of 2019, the world was startled by the emergence of a new disease caused by the Sars CoV-2 virus, now known as Coronavirus Disease-19 (Covid-19). The manufacturing sector is one of the industries affected by the onset of Covid-19 in Indonesia. Covid-19 forced manufacturing companies to lay off employees and caused a decline in the Manufacturing Purchasing Managers Index in 2020. This research aims to analyze the financial performance of manufacturing companies in Indonesia, specifically focusing on profitability ratios before and during the Covid-19 pandemic in 2020. This study is a quantitative research type using descriptive analysis. The hypothesis testing in this research utilizes non-parametric statistical analysis techniques, employing the Wilcoxon Signed Rank Test approach with the statistical tool SPSS version 25.0. The results of the research indicate that Net Profit Margin (NPM), Return On Asset (ROA), and Return On Equity (ROE) before Covid-19 in 2019 were better compared to Net Profit Margin (NPM), Return On Asset (ROA), and Return On Equity (ROE) during the Covid-19 pandemic in 2020 for manufacturing companies in Indonesia.