Statistical Techniques Research Articles

Arctic Wind, Sea Ice, and the Corresponding Characteristic Relationship

In efforts to fulfill the objectives of taking part in pragmatic cooperation in the Arctic, constructing the “Silk Road on Ice”, and ensuring ships’ safety and risk assessment in the Arctic, the two biggest hazards, which concern ships’ navigation in the Arctic, are wind and sea ice. Sea ice can result in a ship being besieged or crashing into an iceberg, endangering both human and property safety. Meanwhile, light winds can assist ships in breaking free of a sea-ice siege, whereas strong winds can hinder ships’ navigation. In this work, we first calculated the spatial and temporal characteristics of a number of indicators, including Arctic wind speed, sea-ice density, the frequency of different wind directions, the frequency of a sea-ice density of less than 20%, the frequency of strong winds of force six or above, etc. Using the ERA5 wind field and the SSMI/S sea-ice data, and applying statistical techniques, we then conducted a joint analysis to determine the correlation coefficients between the frequencies of various wind directions, the frequency of strong winds and its impact on the density of sea ice, the frequency of a sea-ice concentration (SIC) of less than 20%, and the correlation coefficient between winds and sea-ice density. In doing so, we determined importance of factoring the wind’s contribution into sea-ice analysis.

Use of image analysis in the evaluation of radicular nodules in chickpeas

The use of advanced computational systems facilitates the application of a wide range of statistical techniques, available in open-source format, to perform analyses of substantial complexity in biological systems, particularly in the field of plant biology. The aim of this study is to demonstrate the application of image analysis in the evaluation of root nodules in Cicer arietinum plants. The research was conducted in the field, where roots were collected, subjected to rigorous cleaning protocols and subsequently photographed under precisely controlled studio conditions. This photographic process was performed using equipment configured with meticulous parameter settings. Subsequently, image analyses were performed using the statistical software package, R. Parameters of interest were quantified, including metrics such as root area, nodule area, the proportional representation of nodules in relation to the total root mass and the absolute count of nodules present. A critical comparison between the proposed analytical methodology and conventional approaches evidenced a substantial improvement in efficiency, thus highlighting the robustness and validity of this analytical framework for the outlined research objectives. Therefore, the developed methodology has significant potential to facilitate accurate and comprehensive analyses of nodules and root systems, thus making a notable contribution to fostering a deeper understanding and exploration of plant-microorganism interactions. Furthermore, this methodological advancement has the potential to contribute to reducing operational costs and optimizing the time spent on such meticulous evaluative undertakings.

Comprehensive monitoring of contamination and ecological-health risk assessment of potentially harmful elements in surface water of Maroon-Jarahi sub-basin of the Persian Gulf, Iran.

The increase in heavy metal concentration in water bodies due to rapid industrial and socio-economic development significantly threatens ecological and human health. This study evaluated metal pollution and related risks to ecology and human health in the Maroon-Jarahi river sub-basin in the Persian Gulf and Oman Sea basin, southwest Iran, using various indicators. A total of 70 water samples were taken from the sampling sites in the Maroon, Allah, and Jarahi sub-basins and analyzed for nine heavy metals. According to the results, the mean concentration of metals in the sampling locations across the entire sub-basin of Maroon-Jarahi was observed as follows Iron (528.22µg/L), zinc (292.62µg/L), manganese (56.47µg/L), copper (36.23µg/L), chromium (11.78µg/L), arsenic (7.09µg/L), lead (3.43µg/L), nickel (3.23µg/L), and cadmium (1.38µg/L). Most of the metals were detected at the highest concentration in the sub-basin of the Jarahi River. The Water Quality Index (WQI) index in the basin varied from 18.74 to 22.88, indicating well to excellent quality. However, the investigation of the pollution status at the monitoring stations, based on the classification of Degree of Contamination (CD) and Heavy Metal Pollution Index (HPI) indices, revealed that they are in the category of relatively high pollution (16 < CD < 32) to very high (32 ≤ CD), and in the low pollution category (HPI < 15) to high pollution (HPI < 30), respectively. According to the three sub-basins, the highest amount of WQI, HPI, and Cd was observed in the stations located in the sub-basins of the Jarahi River. The calculation of Heavy Metal Evaluation Index (HEI) also indicated that only 10% of the monitoring stations are in moderate pollution (10 < HEI < 20), while in other monitoring stations the HEI level is less than 10. The Potential ecological risk factors ( ) of an individual metal was obtained as follows: Cd (173.70) > As (131.99) > Zn (57.52) > Cu (55.39) > Ni (48.98) > Cr (21.57) > Pb (0.71), revealing that Cd and As are the main elements responsible for creating ecological risk in the studied area. The Maroon-Jarahi watershed included areas with ecological risks that ranged from low (PERI ≤ 150) to very high (PERI ≥ 600). HI and ILCR health indicators indicated that consumption and long-term contact with river water in the study area can cause potential risks to human health, especially children. Moreover, the findings, the highest level of pollution and health risk for both children and adults, considering both exposure routes, occurred in the Jarahi River sub-basin, suggesting that those who live in the vicinity of the Jarahi River are likely to face more adverse health effects. In addition, the findings of the evaluation of the relationship between land use patterns and water quality in the studied basin showed that agricultural lands acts as a main source of pollutants, but forest lands play an important role in the deposition of pollutants and the protection of water quality at the basin scale. In general, the results of pollution indicators, risk assessment, and statistical techniques suggest that the lower sub-basin, the Jarahi area, and the Shadegan wetland are the most polluted areas in the investigated sub-basin due to excessive discharge of agricultural runoff, industrialization, and rapid urbanization. Thus, special measures should be considered to reduce the risks of HMs pollution in the sub-basin of the Maroon-Jarahi watershed, especially its downstream and the impact of agricultural land use on water quality should be taken into consideration in basin management plans.

Causal pathways in preeclampsia: a Mendelian randomization study in European populations.

Our study utilizes Mendelian Randomization (MR) to explore the causal relationships between a range of risk factors and preeclampsia, a major contributor to maternal and perinatal morbidity and mortality. Employing the Inverse Variance Weighting (IVW) approach, we conducted a comprehensive multi-exposure MR study analyzing genetic variants linked to 25 risk factors including metabolic disorders, circulating lipid levels, immune and inflammatory responses, lifestyle choices, and bone metabolism. We applied rigorous statistical techniques such as sensitivity analyses, Cochran's Q test, MR Egger regression, funnel plots, and leave-one-out sensitivity analysis to address potential biases like pleiotropy and population stratification. Our analysis included 267,242 individuals, focusing on European ancestries and involving 2,355 patients with preeclampsia. We identified strong genetic associations linking increased preeclampsia risk with factors such as hyperthyroidism, BMI, type 2 diabetes, and elevated serum uric acid levels. Conversely, no significant causal links were found with gestational diabetes, total cholesterol, sleep duration, and bone mineral density, suggesting areas for further investigation. A notable finding was the causal relationship between systemic lupus erythematosus and increased preeclampsia risk, highlighting the significant role of immune and inflammatory responses. This extensive MR study sheds light on the complex etiology of preeclampsia, underscoring the causal impact of specific metabolic, lipid, immune, lifestyle, and bone metabolism factors. Our findings advocate for a multidimensional approach to better understand and manage preeclampsia, paving the way for future research to develop targeted preventive and therapeutic strategies.

Water Treatment: Evaluation of Maleic Acid-Acrylamide Copolymer Inhibitor Efficiency on Calcite Scale by Response Surface Methodology

Mineral scales of calcite are common in the oil field and pose a serious integrity problem in the wellbore, flow lines, and equipment. It is also a challenge faced by industries such as refineries and power plants. Scale deposition is a complex process depending on various factors such as concentration of scaling species, temperature, pH, and flow rates. Deterministic models are used to predict the scale formation from the level of supersaturation of the scaling species in the water at the operating conditions. However, due to the complexity of the interaction of variables affecting the scaling and inhibition by chemicals, it is suitable to be represented by statistical models. This work focused on applying statistical analysis techniques such as response surface methodology to understand the effect of different operating parameters on the inhibition efficiency of maleic acid-acrylamide copolymer on CaCO3 scales. The copolymer was synthesized, and its inhibition efficiency on the calcite scale was tested using static jar tests at different pH, temperature, and inhibitor concentrations. The effect of the critical parameters on the inhibition efficiency was analyzed using the statistical technique of Response Surface Methodology (RSM). The design of experiments (DoE) was created using a Box–Behnken design with three levels for each factor. The linear and the quadratic effects of the factors were studied and the interaction effects were analyzed using analyses of variance (ANOVA) and RSM. A desirability function was used to optimize the performance for the combination of the variables. The analysis showed that the linear effect of the parameters had the highest impact on the inhibition efficiency. Significant interaction effects were also identified between the operating variables. A transfer function was used to model the experimental data of inhibitor performance.

Enterprise Resource Planning Implementation: Challenges and Barriers

The goal of this study is to ascertain how Enterprise Resource Planning (ERP) adoption software is affected in small and medium-sized businesses in Jordan by the problems and barriers represented by (low knowledge of ERP, misperception, lack of resources, financial worries, and employee resistance). The following titles of employees in Jordanian small and medium-sized businesses' departments of information technology made up the study population: (Department Manager, Assistant Department Manager, Head of Department, and Software Officer). To accomplish the goals of the study, the investigator employed a basic random sample of the study population, wherein (160) questionnaires were distributed and (152) were retrieved. The descriptiveanalytic approach was employed in conjunction with various statistical techniques, the most notable of which was the "T" test for one sample (One SampleT–test), and the statistical package program was utilized for statistical analysis and testing of hypotheses. Use SPSS. The study's conclusions include the existence of a statistically significant relationship between Jordanian SMEs' software implementation and their lack of resources, financial concerns, and inadequate ERP understanding. On the other hand, misperception and employee resistance had no statistically significant effect on the implementation of software in Jordanian SMEs. In light of this, the study made several recommendations, the most significant of which is the establishment of an independent committee of senior management experts in information systems and information technology to monitor a variety of data regarding the readiness and effectiveness of the software. As well as involving the user in the ERP implementation from the beginning, because operations management may clearly and effectively benefit from the end-user's assistance in formulating operations that accurately and firmly fulfil daily work needs

Attitudes of sport parents towards children's eating habits

Today, parents have assumed important roles in shaping their children's eating habits in social and daily life. Especially the tendency of parents who do sports to transfer their healthy lifestyles to their children has positive effects on children's eating habits. This study examines the attitudes of parents on this issue and the effects of these attitudes on children's eating habits. In line with the aim of the study, the attitudes of parents who do sports towards their children's eating habits were investigated. The rationale of the study is to focus on how parents' attitudes towards nutrition affect their children's eating habits and the contribution of these attitudes to children's general health and sports performance. The findings of the study show that parents' nutrition attitudes are critical for children to develop a healthy lifestyle. This study was conducted between 2023-2024 and 860 parents and their children participated in the study. The data obtained from the study were collected using a 5-point Likert-type scale form with validity and reliability and analysed with SPSS 22.0 software. Various statistical techniques such as descriptive statistics, reliability analysis, independent sample t-test, ANOVA, factor and regression analyses were used in the study. The findings obtained at the end of the research show that parents' nutritional attitudes have significant effects on children's eating habits. Parents' attitudes towards healthy eating and physical activity positively affect children's eating habits. Children of parents who do sports develop healthier eating habits, are more active and take part in physical activities. The study reveals that parents' nutritional attitudes contribute to children's general health and sports performance.

An Empirical Analysis of Growth Trends and Correlations among Life Funds, Pension &amp; General Annuity Funds, and ULIP Funds in the Indian Life Insurance Industry

Purpose: This study aims to analyze the growth trends and correlations among three key fund types in the Indian life insurance industry: Life Funds, Pension &amp; General Annuity Funds, and Unit-Linked Insurance Plans (ULIP) Funds. Explicitly, this study intends to answer the resulting research questions: • Which fund type has exhibited the highest AUM growth rate? • What are the key factors contributing to the growth of each fund type? • What are the implications of the findings for the Indian life insurance industry? Design/methodology/approach: The study employs a quantitative research methodology, focusing on historical data spanning from 2014 to 2023. By using statistical techniques such as Analysis of Variance (ANOVA) and correlation analysis, the research identifies and evaluates the significant differences and relationships among the various fund types. ANOVA is used to determine if there are statistically significant differences in growth rates among the funds, while correlation analysis helps in understanding the strength and direction of relationships between the funds. Findings: The analysis uncovers significant disparities in the growth rates of the different fund types. Specifically, Pension &amp; General Annuity Funds demonstrate the highest growth rate among the three. Additionally, the study finds a weak positive correlation between Life Funds and ULIP Funds, indicating a slight tendency for these two fund types to grow together, although the relationship is not strong. Originality/value: This research contributes novel insights into the Indian life insurance industry by showcasing the distinct growth patterns and interrelationships among Life Funds, Pension &amp; General Annuity Funds, and ULIP Funds. The findings are valuable for stakeholders in the industry, as they can inform strategic decisions related to investment, product development, and marketing. By understanding these trends and correlations, life insurance companies can better tailor their offerings to meet market demands and optimize their growth strategies. Key words: Life insurance industry, growth trends, correlations, fund types, investment decisions, product development, marketing strategies.

Secondary School EFL Teachers' Awareness for Formative Assessment for Effective Learning

The aim of this study was to examine the extent to which English as a Foreign Language (EFL) teachers in secondary schools were aware of formative assessment for effective learning, and whether this awareness level differed based on their teaching experience. The study used a survey design, collecting both quantitative and qualitative data from 167 participants, and analyzed the data using various statistical and analytical techniques. The results of the study indicated that EFL teachers had limited knowledge of formative assessment and that their practical understanding of the topic had not been addressed in teacher education curriculums or training programs. The study recommends that educational authorities, such as the Ministry of Education (MOE), teacher education institutions, and universities, take steps to promote the practicality of formative assessment in teacher education programs and on-the-job learning initiatives. The findings of this study can also serve as a reference point for further research and interventions to improve the effectiveness of EFL teacher education in different contexts.

Uranium Mine Proposed Experimental Design for Natural Background Gross Gamma Exposure Rates, Post Remediation Final Status Survey Sampling Density, and Radiological Water Quality Modeling for a Worst-case Catastrophic Failure, Coles Hill, Virginia.

Completely randomized experimental design statistical modeling techniques were employed to analyze exposure rate measurements for evaluating hypothetical natural background post uranium mill operations at Coles Hill, Virginia uranium milling processes. The proposed Coles Hill Uranium Mine is situated upstream of the Banister River. This River is nearly homogenous throughout the reach length used in analysis and feeds into the mouth of Kerr Reservoir, Lake Gaston, which serves as the main drinking water source for cities in the Hampton Roads area including Norfolk, Virginia Beach, and Chesapeake. A critical scan value (=DCGLscan) was developed to flag anomalies of surface contamination during simulated post remediation final status surveys. The natural background was critical for meeting the Multi-Agency Radiation Survey and Site Investigation Manual guidance for post remediation final status surveys. The overarching null hypothesis suggested that the selected mean natural background is equal to the survey unit's mean natural background. Using SAS Procedures Shapiro-Wilk Test, ANOVA, and CR, it was decided the exposure rate data was normal, had no extreme outliers, and no collinearity between the number of samples (=treatment) and the areas (=block). Using the q-hyper (hypergeometric) distribution, the soil sampling density was decided for a final status survey unit. The most likely worst-case catastrophic failure analysis, 500-year event, such as the1969 Hurricane Camille of 69 centimeters of rain in Nelson County, Virginia was included in the model. The model showed impact was minimal at most to the Banister River's drinking water and likely less than the Virginia's Drinking Water Standards for gross alpha, 226Ra and 228Ra, and total uranium.

Impact of the Supply Chain on Sustainable and Business Performance During the COVID-19 Pandemic

The main objective of this empirical study is to provide empirical evidence that allows quantifying the impact of the supply chain on sustainable and firm performance during the COVID-19 pandemic. An electronic survey was applied to collect information on 65 manufacturing firms selected through simple random sampling, using the statistical technique of Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the data obtained using the SmartPLS 4.0 software. Furthermore, the analysis carried out in this study identifies a need for more theoretical and, above all, empirical evidence in this area, which prevents the generalization of the results obtained. Likewise, the results suggest that during the COVID-19 pandemic, the supply chain positively impacted sustainable performance. However, an adverse effect was also detected on firm performance, so it is possible to conclude that the COVID-10 pandemic substantially improved the sustainable performance of manufacturing companies. However, it also generated a decrease in their level of firm performance.

Genotype x Environment Interaction and Yield Stability of Soybean (Glycine max) Genotypes in Multi-Environment Trials (METs) in Nigeria

Genotype x environment interaction (GEI) poses a critical challenge to plant breeders by complicating the identification of stable variety (ies) for performance across diverse environments. GGE biplot and AMMI analyses have been identified as the most effective and appropriate statistical techniques for identifying stable and high-performing genotypes across diverse environments. The objective of this study was to identify widely adapted and high-yielding soybean genotypes from Multi-Locational Trials (MLTs) using GGE biplot and AMMI biplot analysis models. Fifteen IITA-bred elite soybean lines and three standard checks were evaluated for stability of performance in a 3 x 6 alpha lattice design with three replications across seven locations in Nigeria. Significant (p < 0.001) differences were detected among genotypes, environments, and GEI for grain yield, which ranged between 979.8 kg ha-1 and 3645 kg ha-1 with a mean of 2324 kg ha-1. To assess the stability of genotypes, analyses were conducted using the general linear method, GGE, and the Additive Main Effect and Multiplicative Interaction (AMMI) approach, as well as WAAS and ASV rank indices. In the GGE biplot model, the first two principal components accounted for 67.4% of the total variation, while in the AMMI model, the first two Interaction Principal Component Axes (IPCA1 and IPCA2) explained 73.20% and 11.40% of the variation attributed to genotype by environment interaction, respectively. GGE biplot identified G10 and G16 as the most stable and productive genotypes, while WAASB index revealed G16, G10, G9, G4 and G2 as the most adaptive, stable and productive genotypes across locations, and ASV identified G9, G13, G4, G14 and G10 as the most stable and productive.Consequently, genotypes G2, G4, G9, G10 and G16 displayed outstanding and stable grain yield performance across the test locations and are, therefore, recommended for release as new soybean varieties suitable for cultivation in the respective mega environment where they performed best. More importantly, the two genotypes are recommended for recycling as breeding sources for high-yield and yield stability genes, and as parental lines for high-yield and stable performance for future breeding and genomic selection.

Investigating Elementary Teachers' Perceptions of Traditional Science Teaching Methods within the Single National Curriculum Framework

This study investigates elementary teachers' perceptions of traditional science teaching methods within the Single National Curriculum (SNC) at the elementary level. The primary objectives were to evaluate the science achievement of Grade IV students using both cooperative and traditional teaching methods, to compare the effectiveness of these methods based on students' ability levels, and to assess their impact across different science content areas. The study involved 69 elementary teachers, who provided data through a self-developed questionnaire, validated and tested for reliability using Cronbach’s Alpha during a pilot study. The data, collected via oral explanations followed by questionnaire completion, were analysed using statistical techniques such as mean and standard deviation. The findings reveal a preference among some teachers for traditional methods, citing their effectiveness in content delivery. However, there is also recognition of the need to enhance these methods with innovative techniques to improve student engagement and understanding. The study recommends refining traditional teaching approaches by integrating technology and experiential learning opportunities, ensuring a more comprehensive and effective science education experience for elementary students within the SNC framework.

Inclusive tourism: A driving force for collaborative governance in advancing sustainable village tourism

This study aims to investigate the relationship between collaborative governance inclusive tourism in fostering sustainable tourism development in Bali. Employing a quantitative approach, data was collected from a comprehensive sample of 137 tourism villages across in Bali. This study implemented Partial Least Squares-Structural Equation Modeling (PLS-SEM) as a robust statistical methodology technique to analyze the relationship between collaborative governance, inclusive tourism, and sustainable tourism. This study draws upon the tenets of Collaboration Theory, which underscores the critical role of collaboration in realizing sustainable tourism villages. The findings of this research reveal that collaborative governance provides a significant positive influence on sustainable tourism. Notably, this impact is amplified by the moderating effect of inclusive tourism, suggesting that inclusive tourism plays a multifaceted and complex role in the intricate nexus between collaborative governance and sustainable tourism in tourism villages. Overall, the research suggests that the combination of collaborative governance and inclusive tourism is a powerful recipe for sustainable village tourism.

Analysis of Water Quality Data Using Statistical and Artificial Neural Network Techniques

Analysis of Water Quality Data Using Statistical and Artificial Neural Network Techniques

Analysis the Impact of Credit Risk, Liquidity Risk, Management Efficiency on Profitability through Capital in KBMI 4 Banking

This research aims to analyze the influence or impact of credit risk (NPL), liquidity risk (LDR), management efficiency (BOPO) on profitability (ROA) through capital (CAR) as mediating variables in KBMI 4 banking, namely BRI, BCA, BNI and Mandiri Bank. The data collection method is bank annual report data from 2019 - 2023. The analysis method in this research is quantitative analysis, to determine the correlation between variables X1, X2, and X3 to Y and Z as mediating variables. using statistical path analysis techniques and to test the level of significance using the inner model test by looking at the p-value processed with the Smart PLS program. The research results concluded that LDR and BOPO had a negative and significant impact on CAR, BOPO had a negative and significant impact on ROA, NPL had a negative and insignificant impact on ROA. However, NPL has a positive and significant impact on CAR, LDR and CAR have a positive and significant impact on ROA. Apart from that, in testing the indirect effect, the results showed that CAR was able to mediate the influence of the BOPO variable on ROA which had a negative and significant impact. However, the CAR variable is unable to mediate the effect of NPL and LDR on ROA.

Thematic and sentiment analysis of replies to depression help seeking related posts on Sina Weibo

Depression is the most prevalent mental disorder globally, but traditional sources of depression help seeking such as psychiatry are laced with social stigma, resulting in a low worldwide depression professional help seeking rate. In recent years, many with depression have turned to the internet and specifically to social media as an alternative medium to seek help for depression, but the effects of online help have been discovered to be ambiguous. The present study aimed to investigate how depression help seeking related posts are responded to on Chinese social media in terms of two dimensions: themes and sentiments. Employing machine learning statistical techniques including topic modeling and sentiment analysis, this paper assessed the themes and sentiments within 8027 responses to 648 depression help seeking related posts created between October 1, 2018 and June 30, 2024. Topic modeling results reported that four prevalent themes underlie replies to depression help seeking related posts: Sad emotional support, Empathizing, Advising professional help, and Sharing. These prevalent themes all reflected supportive attitudes towards depression help seeking related posts through diverse ways. Sentiment analysis, on the other hand, revealed that still, 18.34% of responses held negative sentiments toward depression help seeking related posts. However, the prevalent sentiment in responses was also discovered to be positive, in line with the results of topic modeling. 78.04% of replies were found to hold positive sentiment, 3.63% of replies were found to hold neutral sentiment, and the mean sentiment score of responses was also positive. The findings of the present study provide insight into how depression help seeking is reacted to in Chinas social media landscape, indicating possible factors that may hinder the effects of seeking help for depression on social media and suggesting the potential need for systems to foster a more supportive online environment towards depression help seeking on Chinese social media.

MENTAL HEALTH AND COVID-19 PANDEMIC: SURVEY ON URBAN ESTATE POPULATION OF PATIALA DISTRICT

Objective: This study aimed to assess the mental health of students, private employees, and government employees in Punjab, India during the COVID-19 pandemic. The results of this study can aid healthcare professionals and policymakers in creating effective policies that promote mental well-being in the general population.Abstract: This research aimed to assess the mental health status of students, government employees, and private employees during the COVID-19 pandemic. To achieve the purpose of the study calculated descriptive statistics, such as the mean and standard deviation. Following this, a one-way analysis of variance (ANOVA) was conducted to identify any disparities between the groups. Subsequently, a post-hoc test (Scheffe Test) was administered due to unequal group sizes. The Statistical Package for Social Sciences (SPSS) Software Version-23 was utilized for all analyses, with a significance level set at 0.05. The study comprised 301 participants (N=301), consisting of 193 male and 108 female subjects. The participants were divided into three categories: government employees, private employees, and students. The Warwick-Edinburgh Mental Well-being Scale (WEMWBS) 2008 was utilized for data collection through a questionnaire survey method. The researcher created a Google form and distributed it to the participants via email and other social media platforms. The collected data was meticulously recorded and analyzed using descriptive and inferential statistical techniques. The study found that the mental health status of government employees, private employees, and students did not show significant variations. However, it was discovered that the COVID-19 pandemic had a more substantial impact on the mental health status of students compared to the well-being status of individuals in different professions. In conclusion that students were mostly affected due to the covid 19 lock down, so special considerations should be given towards the mental well-being status of students.

A Statistical Technique to Develop a Discriminant Model to Categories Senior Female Cricketers of Gujarat into Batsman and Bowler

A Statistical Technique to Develop a Discriminant Model to Categories Senior Female Cricketers of Gujarat into Batsman and Bowler

The Effect of Financial Literacy and Credit Procedures on Credit Taking Decisions

Purpose: This study aims to determine the effect of Financial Literacy on Credit Decision Making. To assess the effect of Credit Procedures on Credit Taking Decisions. Moreover, to determine the impact of Financial Literacy and Credit Procedures on Credit Decision Making. Research Design and Methodology: The population in this study were debtors of Bank BRI Jayapura City Unit Office who applied for credit in 2021-2022, totaling 1,714 debtors. The sampling technique used in this study is proportional random sampling. Data sources use primary data and secondary data. The statistical analysis method used in this research is Multiple Linear Regression Analysis based on the T Statistical Test technique, F Statistical Test, and the Coefficient of Determination with the help of SPSS version 29 software. Findings and Discussion: The results showed that Financial Literacy has a positive and significant effect on Credit decision-making, and credit procedures have a positive and significant effect on credit decisions. Financial Literacy and Credit Procedures simultaneously affect the decision to take credit at BRI Bank Jayapura City Unit. Implications: This research is expected to significantly influence future studies in economics, particularly financial management. The results are also likely to serve as a reference and comparison material for further research related to credit decision-making.