Statistical Analysis Of Data Research Articles

Women's Representation in Government Bodies of the Russian Federation in the Period from 1991 to 2023

The representation of women in public authorities reflects a number of more general issues related to gender equality, the peculiarities of women's political leadership, women's participation in politics, etc. The purpose of this article was to identify gender proportions in the federal executive authorities and the Federal Assembly of the Russian Federation for the period from 1991 to 2023. The study was conducted by statistical analysis of data presented in open sources, on the websites of the Federation Council, the State Duma, the Government and other public authorities. This article reflects the dynamics of changes in the gender distribution of positions in the field of politics over the period under study. For the analysis, the highest positions of executive and other state authorities of the country were selected, as well as membership in both chambers of the Russian parliament, which made it possible to consider women's representation in positions involving direct decision-making. The study raises the problem of the underrepresentation of women in senior political and elected positions in public administration. According to the results of the study, data on women's representation in government over the past 34 years were systematized. A trend has been identified to increase the representation of women in high-level executive positions. At the same time, the number of women in the Cabinet of Ministers of our country in the entire history of the Russian Federation has not exceeded 11% or two female representatives at the same time. No more than two women at the same time had the opportunity to take the position of Deputy Prime Minister. There are positions that have been held exclusively by men for more than thirty years. The number of women in the country's parliament is also small, but the positive trend here is more pronounced. With a global average of 26.5% female representation, in Russia there are only 18.4% women among the members of both houses of parliament.

WŁADZA NARODOWA PAŃSTWA I SPOSÓB JEJ OCENY NA PRZYKŁADZIE REPUBLIKI AZERBEJDŻANU

This study aims to analyze the national power of the state and its structural components including population, territory, economy, military power, scientific and technical progress, political will, and geopolitical factors. The research problem of the study was focused on estimating the state’s national power. The hypothesis of the study assumes that government policies should be based on real national power in order for policymakers to adopt rational policies. Research methods used in the study include comparative analysis, analysis and synthesis, and statistical data analysis. Additionally, the structural components of national power are reformulated into a new formula by reviewing the calculation rules. Furthermore, a mechanism for measuring the national power of the Republic of Azerbaijan is proposed using a fuzzy numerical scale based on expert opinion.

Методичні аспекти формування облікової політики товарів у системі управління підприємством

The article studies methodological aspects of accounting and controlling goods in enterprises to form an informational foundation for managerial decision-making. The study’s relevance is associated with the widespread nature of trade operations in enterprises across various sectors of economic activity. The statistical data analysis has proven that the volume of trade operations is increasing, and such operations are conducted across different economic sectors. The development of trade activities enhances the importance of goods in enterprise operations, thus underscoring the need to develop theoretical and methodological provisions for accounting and controlling goods. The purpose of the article is to systematize the theoretical and methodological foundations of goods accounting and control and to determine the role of these processes in an enterprise’s operations and overall management system. The role of accounting and control of goods in the management system of an enterprise’s activities is substantiated. It is determined that the quality development of such a system will facilitate the collection of timely and accurate information on inventory and serve as a tool for ensuring the enterprise’s financial stability. The existing methodological foundations of this process have been systematized to enable the development of a goods accounting system for enterprises. Regulatory acts governing the accounting and control of goods operations are summarized in two directions: external and internal. The main aspects of goods accounting regulated by the examined documents are characterized. The main elements of goods accounting policy, which serve as the foundation for forming information support for managerial decisions, are highlighted; thus, enterprise management must develop and coordinate them. The system of accounts for recording transactions involving enterprise goods is specified, along with the correspondence of accounts for reflecting such operations, including the documentary support for their representation. The necessity of goods control is substantiated, and the primary methods for its implementation are specified. The research results can be applied in the practical activities of enterprises to organize a system of accounting and control of goods. Keywords: information support, control, accounting, regulation, goods, managerial decisions.

The synergy of debt management, big data technology and corporate decision-making: A catalyst for enhanced financial performance through operational efficiency and sustainable business strategies

This research explores the impact of debt management and big data technology utilization in management decision-making on corporate financial performance with a focus on operational efficiency and sustainable business strategy effectiveness as intervening variables. It aims to delve into how a firm's debt management strategies and its incorporation of big data into decision-making processes influence its financial outcomes. This study scrutinizes the company's approach to managing its debt structure and levels while the use of big data technology in decision-making reflects the integration of advanced technology in strategic planning by examining debt management. The study further investigates how operational efficiency and the effectiveness of sustainable business strategies act as intermediaries in this relationship indicating the role of a firm's internal processes and corporate strategy in driving financial success. Moreover, the research considers mediating variables such as industry type and market competition level which could affect the relationship between the independent and dependent variables. This study aims to test these relationships providing insights into the influence of debt management and big data technology on financial performance using statistical data analysis. Expected outcomes include a deeper understanding of the strategic implications of these factors for achieving sustainable and improved financial performance in a complex business landscape. Emphasizing the importance of efficient debt management and the strategic application of big data technology, the study highlights the necessity for firms to adopt wise financial resource management and innovative decision-making approaches to navigate the challenges of the modern business environment effectively.

Farmers’ traditional knowledge on seasonal frost management and their tree preferences in frost affected highlands of Amhara region, Ethiopia

Extreme environmental conditions, such as high temperature, frost, low humidity and desiccating winds, are the main causes for the failure of plantation forests in Ethiopia. Frost damage contributes to the low seedling survival and plantation success in frost affected highlands of Amhara region Ethiopia. Research outputs on farmers' traditional knowledge on frost management and technologies that curb frost related problems are limited in the country. This study was conducted to document the farmers’ traditional knowledge on frost management and their tree preference in frost affected highlands of Amhara region. Sinan, Guna-begemder and Meket districts were selected purposively in 2020. One representative sample Kebele was selected in each district with a total of 204 households selected with systematic random sampling technique for interview. In addition to interview focus group discussion was also conducted. Both descriptive and inferential statistics data analysis method were employed. In this study, frost was found to be an important limiting factor for plantation development in the study area. Frost occurs, mainly, from September to January. The local community applies traditional frost management techniques. The seasonality of frost occurrence and type of traditional frost management practices varied among the studied Kebeles. Eucalyptus globulus, Oldeania alpina, Rhamnus prinoides and Chamaecytisus palmensis were preferred trees species due to their frost resistant performance. The effectiveness of identified traditional frost management techniques needs to be investigated before they can be promoting and disseminating. Farmers should also be trained in proper techniques to protect planted seedlings from frost damage. Adjusting the timing of planting may also help to mitigate the effect of frost damage.

Relation between nutrition intake, prediabetes, and central obesity with handgrip strength in Indonesian medical student

Background: Muscles are crucial in creating movement, stabilising body posture, and regulating body temperature. Muscle strength can be assessed using handgrip strength. Handgrip strength can predict muscle function, nutritional status, diabetes risk, and the risk of metabolic syndrome. Handgrip strength can be influenced by muscle mass, nutritional intake, fat mass, physical activity level, and metabolic syndrome. Objective: This research is to find relationship between handgrip strength and nutritional intake, muscle mass, and central obesity. Methods: The research was conducted as a cross-sectional study using observational analytical methods. The sample consisted of 53 individuals selected through purposive sampling. Handgrip strength can be measured using a hand dynamometer, nutritional intake using a 2x24 hour food recall, muscle mass using a body composition analyzer, central obesity using waist to hip ratio, and fasting blood sugar using a glucometer. Statistical data analysis employed the chi-square test and independent T-test. Results: The results indicated a relationship between central obesity and handgrip strength (p = 0.006). Researchers are interested in studying muscle strength and its predictors concerning central obesity, prediabetes, and nutritional status in medical students. The results indicated a relationship between handgrip strength and central obesity (p = 0.006), but no relationship was found between handgrip strength and energy intake (p = 0.235), protein intake (p = 0.524), and prediabetes (p = 0.272). Conclusion: There is a relationship between central obesity and handgrip strength. Future researchers are encouraged to consider additional factors, including physical activity, muscle mass index, and comorbidities.

Predicting Financial Fraud through Pressure, Opportunity, Rationalization and Internal Control (Case Study on Food and Beverage Companies Listed on the IDX)

The Empirical Study of Food and Beverage Companies Listed on the Indonesia Stock Exchange in 2017-2019 aims to explain and forecast the impact of pressure, opportunity, rationalization, and internal control on financial statements that are false. Because it stresses verifying theories using numerical measurements of research variables and statistical data analysis, this study takes a quantitative approach. The study's population consisted of 18 companies that were listed in the food and beverage sub-sector between 2013 and 2017 and were part of the Indonesia Stock Exchange (IDX). Multiple linear regression analysis, often known as multiple regression, is the analysis model that is used to examine how the independent variables affect the dependent variable. The analysis's findings demonstrate how pressure, opportunity, rationalization, and internal control all significantly impact financial statement fraud at the same time. Internal control has little impact on fake financial statements, while pressure, opportunity, and rationalization all have a considerable impact.

Incompatibilities Between Current Practices in Statistical Data Analysis and Differential Privacy

The authors discuss their experience applying differential privacy with a complex data set with the goal of enabling standard approaches to statistical data analysis. They highlight lessons learned and roadblocks encountered, distilling them into incompatibilities between current practices in statistical data analysis and differential privacy that go beyond issues which can be solved with a noisy measurements file. The authors discuss how overcoming these incompatibilities require compromise and a change in either our approach to statistical data analysis or differential privacy that should be addressed head-on.

The Impact of Machine Learning Technology on E-Learning Platforms on Student Learning Behavior

This study aims to determine the influence of Machine Learning Technology on the E-Learning Platform on student learning behavior. This research is a type of meta-analysis research. The data source comes from 10 national journals indexed by SINTA published in 2022-2024. Deep collection technique through direct observation. The process of searching for virgin sources through google scholar, ERIC, and IEEE. Data analysis is statistical data analysis by calculating the effect size value with the help of the JSAP application. The results of the study concluded that the average effect size value was 0.791 in the medium effect size category. These findings explain that there is a significant influence of machine learning technology on e-learning platforms on student learning behavior.

Colorectal Carcinoma: Is There Any Correlation between Her2/neu Expression, Ki-67 Score, and Tumor Budding and Clinicopathological Parameters?—A Prospective Institution-Based Study

Objectives Colorectal cancer is one of the most frequent cancers worldwide and is still a major cause of cancer mortality. Her2/neu, Ki67 score, and tumor budding are independent prognostic factors in colorectal carcinomas. The objectives of the study were to evaluate Her2/neu expression, Ki67 score, and tumor budding index at invasive margin in colorectal carcinoma and find out their possible correlations with different clinicopathological factors. Materials and Methods An institution-based observational cross-sectional study was conducted for 18 months. Forty-one patients with histologically proven diagnosis of colorectal carcinoma were included. Histopathological and immunohistochemical analyses (Her2/neu and Ki-67) of each case were done. Statistical Analysis Data analysis was done using the SPSS software. Results A significant correlation was found between tumor budding status and pathological T stage, Dukes' and American Joint Committee on Cancer stages, and between tumor-infiltrating lymphocytes status and Ki-67 expression status (p < 0.05). Conclusion The prognostic importance of tumor budding in colorectal carcinoma is very clear. Considering the small sample size of the present study, the prognostic values of Her2/neu and Ki-67 are required to be explored further in larger cohorts in the future.

A Novel Classification of Migrated Lumbar Disk Herniation Based on Magnetic Resonance Imaging and Algorithm Recommendations for Full-Endoscopic Discectomy.

Retrospective clinical study. The purpose of this study was to establish a novel classification of migrated lumbar disk herniation (LDH) based on magnetic resonance imaging and provide appropriate treatment strategies for each type through algorithms. Full-endoscopic lumbar discectomy is a surgical technique that has been developed rapidly in recent years. For migrated LDH, few surgeons currently classify it with multiplanar positioning, and there is no consensus on the choice of treatment strategy. Therefore, we established a new multiplanar classification criteria that can localize the lesions more accurately than previous studies. A total of 263 eligible patients from March 2017 to March 2022 were included. Protrusions for each patient were located based on our classification and the surgical approach was selected according to our algorithms. The clinical symptoms of all patients before surgery, and at 1 day, 1 month, 3 months, 6 months, and 12 months after surgery were collected. Evaluations were performed using visual analogue scale (VAS), Oswestry Disability Index (ODI) and modified MacNab criteria. We used the chi-squared test, one-way analysis of variance (ANOVA), and t-test to compare perioperative results and postoperative 3-month, 6-month, and 12-month follow-up results. VAS (low back pain) scores were reduced from 5.33 ± 2.67 to 0.73 ± 0.77 (p < 0.001), and VAS (leg pain) scores were reduced from 7.44 ± 2.21 to 0.37 ± 0.51 (p < 0.001). ODI scores improved from 58.46 ± 8.04 to 12.57 ± 2.51 (p < 0.001). According to the modified MacNab criteria, the excellent and good rate reached 92.78% at the 12-month follow-up. Twenty-six patients developed complications, all of which improved after treatment. Recurrence occurred in 13 patients, and four of them underwent secondary surgery. This is an innovative classification method using multi-plane positioning, and the algorithm used with it can help surgeons make appropriate choices when using endoscopic technology to treat migrated LDH. Statistical analysis of follow-up data confirmed that this is a safe and effective strategy.

The Advancement of Artificial Intelligence's Application in Hybrid Solar and Wind Power Plant Optimization: A Study of the Literature

The harnessing of solar, wind, and hydroelectric energy sources has rendered them easily accessible renewable resources, owing to their abundant availability. There is a growing body of research evincing interest in the deployment of hybrid renewable energy systems. Over recent decades, adopting hybrid technologies has engendered a positive trend, marked by broader considerations of configurations and applications within these systems. This study analytically examines the potential of hybrid solar and wind energy harvesting devices. As such, the project aims to extensively evaluate relevant literature and statistical analysis of data extracted from journal papers published between 2004 and 2023. A specific objective is to develop a complete database matrix surrounding multiple categories, including component configurations, methodological approaches, and supporting software infrastructures. Moreover, an assessment of the socio-economic, environmental, and ecological impacts of these systems is undertaken to ascertain their salience. Furthermore, this inquiry delves into the optimization strategies of these systems leveraging artificial intelligence methodologies. Critical lacunae identified during this review pertain to more emphasis on optimization metrics for PV-wind hybrid energy systems, impeding a holistic understanding of their implications on energy, economics, environment, and society. Our findings underscore prevalent methodologies such as computational modelling utilizing software suites like MATLAB/Simulink, HOMER, and others to derive empirical data. Additionally, parametric analyses emerge as the predominant approach, characterized by the application of algorithms such as Particle Swarm Optimization (PSO), Fuzzy Logic Control (FLC), and Genetic Algorithms (GA), among others. PV-wind hybrid energy systems are classified into autonomous and grid-interconnected configurations, with primary components comprising PV-wind generators. The anticipated trajectory suggests a burgeoning development of these hybrid energy harvesting systems, underpinned by their potential as clean, sustainable, and eco-friendly energy sources.

Biological Reference Intervals for 17α-Hydroxyprogesterone Immunoreactive Trypsinogen, and Biotinidase in Indian Newborns

Neonatal deaths, which usually occur in the first week after delivery, account for nearly 75 percent of all deaths of children under 5 years of age. Prematurity, birth difficulties, infections, and birth defects are responsible for about 40 percent of these deaths. Although mortality rates have declined since 2000, access to quality healthcare remains a major problem for mothers and infants worldwide. In perspective, the present study aimed to establish clear biological reference intervals for 17α-hydroxyprogesterone (17-OHP), immunoreactive trypsinogen (IRT), and biotinidase in Indian neonates. The statistical analysis of data from up to 3200 dried blood spot (DBS) samples of Indian newborns provided valuable information for the new cut-off values in newborn screening (NBS) programs. We applied correlation analysis to fix the relationship for NBS parameters such as 17-OHP, IRT, and biotinidase. This study provided important information about the distribution and comparison of key cut-offs for biomarkers considering body weights and gestational age in the Indian newborn population for the first time, which can help healthcare experts make easier treatment decisions.

Mixed effects models but not t-tests or linear regression detect progression of apathy in Parkinson’s disease over seven years in a cohort: a comparative analysis

IntroductionWhile there is an interest in defining longitudinal change in people with chronic illness like Parkinson’s disease (PD), statistical analysis of longitudinal data is not straightforward for clinical researchers. Here, we aim to demonstrate how the choice of statistical method may influence research outcomes, (e.g., progression in apathy), specifically the size of longitudinal effect estimates, in a cohort.MethodsIn this retrospective longitudinal analysis of 802 people with typical Parkinson’s disease in the Luxembourg Parkinson's study, we compared the mean apathy scores at visit 1 and visit 8 by means of the paired two-sided t-test. Additionally, we analysed the relationship between the visit numbers and the apathy score using linear regression and longitudinal two-level mixed effects models.ResultsMixed effects models were the only method able to detect progression of apathy over time. While the effects estimated for the group comparison and the linear regression were smaller with high p-values (+ 1.016/ 7 years, p = 0.107, -0.056/ 7 years, p = 0.897, respectively), effect estimates for the mixed effects models were positive with a very small p-value, indicating a significant increase in apathy symptoms by + 2.345/ 7 years (p < 0.001).ConclusionThe inappropriate use of paired t-tests and linear regression to analyse longitudinal data can lead to underpowered analyses and an underestimation of longitudinal change. While mixed effects models are not without limitations and need to be altered to model the time sequence between the exposure and the outcome, they are worth considering for longitudinal data analyses. In case this is not possible, limitations of the analytical approach need to be discussed and taken into account in the interpretation.

A prescriptive analytics approach for evaluating two production systems: Simulation optimization algorithm

Production systems influence cost performance and carbon emissions. Environmental concerns compel companies to optimize energy efficiency in their production processes. This study explores the dilemma associated with fixed-time and fixed-lot systems during random disruptions and how these systems can improve performance. We employ simulation optimization models in business analytics using the discrete event simulation provided by the SimPy library within a Python environment. The study is based on the statistical analysis of data collected from 624,000 simulated hours. Our analysis reveals that a higher service level tilts the balance, favoring adopting a fixed-time production system in scenarios characterized by significant disruptions. A system with higher demand variability and lower standalone workstation availability (indicative of more variable production) tends to favor a fixed-time batch production approach. When workstations operate at low-capacity utilization combined with high standalone availability, the fixed-lot batch production system becomes more cost-effective. Overall, the fixed-time system demonstrates a superior capacity to accommodate higher production variability levels than the fixed-lot system. This paper contributes to the existing literature by providing simulation-optimization evidence to assess the relative efficiencies of fixed-size and fixed-time lot batch production systems. This paper considers the impact of random disruptions on operational efficiency within fixed-size lot batch production systems, highlighting the consequences of variability in lot completion times. The study also contributes to strategically selecting production systems to optimize energy usage in manufacturing processes.

Socioeconomic disparities in children's posture defects: a comparison between private and public educational institutions

The topic of risk factors for posture pathology in Polish children is relevant at present, as it is insufficiently studied and reflects the need to investigate the relationship between family socioeconomic status and the occurrence of posture defects, to develop relevant prevention and treatment strategies in the context of current socioeconomic conditions in Poland. The research aims to study posture defects in children depending on their socioeconomic status in the example of private and public schools. A comparison of the prevalence of deformities and posture disorders of participants in private and public educational institutions from 2017 to 2020 is presented. Theoretical research methods (literature analysis, generalisation); empirical methods (study of other researchers' experience), statistical analysis, and graphical presentation of data were used. More than 1300 Polish schoolchildren from private and public schools took part in this cross-sectional study. The most common problems were flat feet (54.73%), calf muscle contracture (44.30%), and valgus deformity (21.22%). The least common problems were funnel chest (0.37%), cavus foot (0.10%), and hammer toe deformity (0.04%). The general trend shows that problems with flat feet and calf muscle contracture were more common among participants in both types of educational institutions. There was a general trend of increasing the number of nosological forms per patient in both private and public institutions over a period of three years. Private institutions had significantly fewer cases of one patient having more than one nosological form as compared to public institutions.

How to Tell Whether Patients Engage and Use a Patient Portal - An Analysis of Five Functions.

The road to a more sustainable healthcare system includes creating a digital interface to the healthcare system that patients can use to engage in their health problems while outside the consultation room. The aim of the study was to evaluate trends in the use of functions in a patient portal and assess which functions were most likely to contribute to sustainable healthcare. Open, uncontrolled retrospective analysis of citizens' use of the patient portal. Extraction and statistical analysis of log data. Log analysis revealed that patients engaged with the patient portal to make appointments, fill out and submit questionnaires, send messages to their care provider, inspect their laboratory results, and view notes about themselves. The functions that displayed a significantly increasing trend were the number of appointments made, the number of messages sent, and the number of checked test results. While portal engagement can reduce patient dependency on healthcare services, external factors also influence this outcome. Further research is needed to investigate which functions support healthcare sustainability and enhance patient empowerment, possibly through other study designs.

Modelling a financial literacy strategy as a life project concept

Financial literacy as a key element of ensuring sustainability and stability of economic systems is becoming important in the process of economic development. Financial literacy contributes to improving the well-being of citizens and the efficiency of financial resource management at the macro level. Thus, the purpose of the present study was to develop models for evaluating the effectiveness of various financial literacy strategies and their impact on the formation of life projects. A complex of scientific methods, including the analysis of statistical data and modelling of financial behaviour, was used to create a strategic model of financial literacy as a concept of a life project. A methodological approach, encompassing the decomposition of the stages of a person’s life and the identification of the peculiarities, connected with the use of money at each of these stages, was implemented in the research. Approaches to financial literacy focused on various forms of interaction with financial resources were suggested, and effective strategies for improving financial literacy were identified. The concept of financial literacy was examined and specified through the lens of knowledge, skills, and confidence for making responsible financial decisions. The advantages and disadvantages of developing financial literacy in Ukraine were identified, and examples of successful strategies of leading countries were provided. The importance of financial education at different stages of a person’s life was substantiated; the key periods of a person’s life and development, when money can act as earnings, expenses, accumulation, preservation, and transfer, were specified. The assessment of the influence of financial literacy on economic behaviour was carried out, and a life project model that takes into account financial decisions and actions was developed. Monetary models of preservation and accumulation of parental income, pocket money, and earnings from employment were considered in detail. The results of this study can be applied in practice when creating a state strategy aimed at increasing the level of financial literacy of the population and ensuring economic security

The analysis for fatigue caused by vibration of railway composite beam considering time-dependent effect

The time-dependent effects in steel-concrete composite beam bridges can intensify track irregularities, subsequently leading to amplified train-bridge coupling vibrations. This phenomenon may increase the stress amplitudes in the bridge steel, thereby impacting the fatigue performance of the composite structures. This paper employs multiple rigid body dynamics to construct a high-speed train model and utilizes the finite element method to develop a steel-concrete composite beam element model that accounts for time-dependent effects, interfacial slip, and shear hysteresis. This approach enables the computational analysis of the train-bridge coupling system, facilitating an investigation into the influence of concrete’s time-dependent effects on the fatigue performance of railway steel-concrete composite bridges. Focusing on a 40-m simply supported composite bridge, the train-bridge coupling dynamic responses were computed for each operational year within a decade of the completion of construction. Applying the P-M linear fatigue damage accumulation theory, statistical analysis of stress history data across various operational periods was conducted to quantify the fatigue damage induced by a single eight-car high-speed train on the lower flange of the mid-span steel beam and the beam-end studs. The findings reveal that the beam-end studs sustain greater damage than the mid-span steel beam. Moreover, the detrimental impact of time-dependent effects diminishes with the increase of operational years. Notably, compared to the initial year, the fatigue damage to the lower flange of the mid-span steel beam by an eight-car train in the tenth year has surged by 39.3%. Conversely, the damage to the beam-end studs has decreased by 47.5%.

Hubungan Pendidikan Agama Kristen dan Budi Pekerti dengan Etika Kepribadian Siswa Siswi Kelas VII SMP Negeri 4 Balige Kabupaten Toba Tahun 2024

Christian Religious Education and Ethics is the government's effort through education to have a good impact on students' personality ethics. However, in the development of today's times, the ethics of students' personalities are getting worse so that they cause deviations. That is what makes the author feel interested and encouraged to conduct research on the relationship between Christian Religious Education and Ethics with the personality ethics of SMP Negeri 4 Balige students in 2024. This study aims to determine the relationship between Christian Religious Education and Ethics with the personality ethics of students in grade VIII of SMP Negeri 4 Balige in 2024. The research method used is a quantitative approach with inferential statistical data analysis. The population in this study is all grade VIII students of SMP Negeri 4 Balige which totals 208 students consisting of seven classes. Sampling in this study uses the probability sampling technique, which provides the same opportunity for each population to be selected as a sample member. The sample of this study was 62 people. The results of the research obtained using the r test are r_(count) &gt; r_(table), which is 0.658 &gt; 0.254 and the t-test t_(count) &gt; t_(table), which is 6.769 &gt; 2,000, it shows that there is a strong, positive and significant relationship between Christian Religious Education and Ethics and the personality ethics of students in grade VIII of SMP Negeri 4 Balige in 2024. In the determination coefficient test, data results of 43.3% were obtained which could be explained by Christian Religious Education and Ethics, while 56.7% were explained by other variables that were not researched by the researcher. This study is a recommendation for future researchers to research other variables related to student personality ethics using research methods and data collection tools that are more optimal.