Statistical Tools Research Articles

A Study on Agri-preneurial Behaviour of Kalanamak Rice Growers in Siddharth Nagar and Sant Kabir Nagar District of Uttar Pradesh, India

Kalanamak rice, hailed for its nutritional potency and health benefits, presents a promising avenue for alleviating these challenges. This study, titled “A Study on Agri- preneurial Behaviour of Kalanamak Rice Growers in Siddharth Nagar and Sant Kabir Nagar District of Uttar Pradesh, India,” delves into this potential within the precincts of Siddharth Nagar and Sant Kabir Nagar district. The investigation hones in on two blocks – Birdpur in Siddharth Nagar, and Santha in Sant Kabir Nagar. Methodologically rigorous, the study selected six villages from each block and engaged with a total of 120 Kalanamak growers. Data collection unfurled through personalized interviews, facilitated by a meticulously crafted questionnaire. To unravel patterns and nuances, statistical tools such as frequency, percentage, mean, and standard deviation orchestrated the classification of data. The coefficient of correlation `r` was invoked to fathom the interplay between Kalanamak growers` attributes, their knowledge, and their adoption of Kalanamak rice. Analysis of the respondent demographics spotlighted several noteworthy trends. A preponderance (70.83%) emerged from the middle age group, with educational attainments peaking at the middle school (34.17%). In terms of occupation, 45% were engaged in agriculture, The agrarian landscape was marked by a significant representation from the Other Backward Classes (OBC) category (49.17%), Landholding skewed towards the smaller end (49.17%), Family dynamics, as reflected in size and structure, were characterized by medium level (64.17% and 90.83%, respectively).

Optimizing Patient Recruitment in Global Clinical Trials using Nature-Inspired Metaheuristics

A common problem seen in the ineffective execution of global multicenter trials is the frequent inability to recruit a sufficient number of patients. A myriad of barriers to recruiting enough patients timely exist and may include practical limits on the number of recruiting sites imposed by the various countries, as well as administrative, cost and unanticipated issues. The Poisson-gamma recruitment model is a widely accepted statistical tool used to predict and track recruitment at different levels of a trial and make inference. An optimal recruitment plan can be designed using mathematical optimization, however, the search is complicated with multiple nonlinear objectives and constraints that arise from regulatory and budgetary considerations. We review nature-inspired metaheuristic algorithms which are powerful, flexible, general purpose optimization tools and demonstrate their capability and utility in optimizing complex recruitment designs for global clinical trials using the Poisson-gamma model as an exemplary model. This research opens up new avenues for improving the efficiency and effectiveness of patient recruitment in clinical trials, thereby potentially accelerating the development of new medical treatments.

Dance Pedagogy used by Physical Education Teachers in Enhancing Skill Acquisition, Mastery and Self-Image

Effective teaching practices in dance cover a variety of theoretical and practical approaches and techniques and individual teaching and learning styles. This study focused on dance pedagogy used by physical education teachers in enhancing skill acquisition, mastery, and self-image. Specifically, the study investigated the extent of the use of dance pedagogy by physical education teachers in five teacher education institutions to enhance skill acquisition, mastery, and self-image. The total number of participants of the study was twenty-three (23) wherein fifteen (15) were females and eight (8) males and with experiences in teaching ranging from 1 to 25 years. A questionnaire comprising 65 items that exemplify the sixteen dance teaching guidelines for strengthening students' dance skill acquisition, knowledge, and self-image was used to gather data supported by classroom observation. The items were adapted from the sixteen guidelines for teaching and learning identified by Mainwaring and Krasnow, which were categorized into three major areas: process and goals, influences that affect dancers' progress, and structure and content of the class. The data were treated using descriptive statistical tools. The results showed that the physical education teachers always practice dance pedagogies that enhance dance skill acquisition, mastery, and self-image. Dance pedagogies are needed to maximize the potential of every learner who wants to progress and become their best.

Factors Affecting Acceptance of Caesarean Section among Childbearing Age Women in Ebute-Metta, Lagos Mainland Local Government in Lagos State, Nigeria

The research study was centered on investigating the factors affecting the acceptance of CS among childbearing age women in Ebute-Metta, Mainland Local Government of Lagos State, Nigeria. The descriptive survey design and simple random sampling and purposive sampling technique was used to elicit information from 138 women attending Antenatal Clinic in Federal Medical Centre, Ebute Metta; State Health Centre, Ebute Metta; Primary Health Care Centre; St. Annes Infirmary for Women, Dawodu Lane, Ebute-Metta; Redeemed Christian Church of God Maternity Centre, Ebute Metta, out of which 129 was returned and dully filled. Data was analyzed using frequency tables, percentage, mean and Standard Deviation. Chi-Square statistical tool was used to test hypotheses. Result revealed that 94.6% of the respondents have high knowledge of CS as a method of delivery. 30.3% of the respondents agreed that CS is preferable to vaginal delivery as the pain in vaginal delivery is usually unpleasant, 55% agree that CS cost more than vaginal delivery. 49.7% of the respondents have experienced CS. Statistically, Knowledge of CS will significantly affect acceptance of CS among women of Childbearing age at X2= 65.163; df=22; p-value 0.000<0.05. Cultural belief will significantly affect acceptance of CS among women of Childbearing age at (X2= 88.271; df= 43; P-value 0.000<0.05. It was therefore concluded that Mothers should therefore be educated on the process involved in Caesarean Section delivery and the advantage, causes, importance of this method of delivery in saving the life of mother and baby. It was recommended that a well-organized and structured education / counselling session be organised during antenatal visit in order to help increase useful information about Caesarean section.

Impact of TQM on operational, logistical and quality performance with a moderating role of reverse supply chain

Many research studies established the significance of total quality management to organizational performance. However, most of the researchers focused on individual relationships. This research aims to examine an integrated model by analyzing the impact of total quality management on operational performance, logistics performance, and quality performance with moderation of revere supply chain in steel companies of Pakistan. The study used a quantitative research method to test the hypotheses by collecting data utilizing the survey questionnaire on a five-point Likert scale. For analysis, the study opted for IBM SPSS and SmartPLS as the appropriate statistical tools. This study confirms the significant relationship between total quality management and reverse supply chain. Furthermore, this study finds no significant relationship between comprehensive quality management and operational, logistics, and quality performance. The insignificance values show the lack of implementation of study variables in the study and the geological context.

Comparative Analysis of Returns and Standard Deviations of Healthcare Companies’ Stocks: a Five-year Study (2019-2023)

This research conducts a comparative analysis of returns and standard deviations of healthcare companies’ stocks listed on the National Stock Exchange (NSE) over a five-year period from 2019 to 2023. The study aims to provide valuable insights for investors in the health sector, assisting them in balancing risk and return in their investment decisions. Secondary data sourced from the NSE website, publications, and journals is utilized, employing a descriptive research design. Statistical tools such as returns, beta, and standard deviation are used to analyze the data. The objectives include examining mean returns, assessing risk levels, contrasting achievements among healthcare corporations, and recommending suitable securities for investors. The findings offer actionable insights for investors aiming to optimize their investment outcomes within the healthcare industry. The investigations examines to the comparisons between healthcare companies’ stocks on NSE from 2019 to 2023. The intent is to assist with making informed decisions. Secondary data was collected from various sources, utilizing a descriptive design. Statistical tools such as returns; beta and standard deviation are applied to interpret the information. Key objectives include examining mean returns, evaluating risk, and recommending securities for investors. The results aim to provide useful recommendations for investment within the healthcare sector!.

Time-Series Forecasting of a Typical PWR Undergoing Large Break LOCA

In this work, a machine learning (ML) metamodel is developed for the time-series forecasting of a typical nuclear power plant response undergoing a loss of coolant accident (LOCA). The plant model of choice is based on the APR1400 nuclear reactor. The key systems and components of APR1400 relevant to the investigated scenario are modelled using the thermal-hydraulic code, RELAP5/MOD3.4, following the description published in the design control document. The model is tested under a spectrum of initial and boundary conditions via propagation of key uncertain parameters (UPs) which are derived from the phenomena identification and ranking table (PIRT). This is achieved by loosely coupling RELAP5/MOD3.4 with the statistical tool, Dakota. The most probable nuclear power plant (NPP) response was calculated using the best estimate plus uncertainty (BEPU) approach. Next, the database generated from the NPP system response was used as an input for the ML model. The NPP system response was represented by peak cladding temperature (PCT), safety injection system (SIT), mass flow rate, reactor power, and primary system pressure. In this research, two regression models were tested with reasonably good performance, namely, the gated recurrent unit (GRU) and the long short-term memory (LSTM).

The Mediating Effect of Stress Management Competency on the Relationship between Job Satisfaction and Employee Attrition: Evidence in a Local Government Unit

Purpose: The workforce or manpower is one of the 4Ms of production and is considered the most critical factor of production. It is the employees who determine whether the organization succeeds or fails. The primary goal of this study was to determine the mediating effect of stress management competency on the relationship between job satisfaction and employee attrition.
 Materials and Methods: A non-experimental quantitative research design was used, specifically the descriptive-correlational and mediation approaches. A face-to-face survey was used to obtain data. The data were obtained from 322 City Environment and Natural Resources employees, including regular and contractual employees, job orders, and allied service personnel selected through stratified random sampling. The statistical tools used to analyze and interpret the data were descriptive statistics, Pearson’s R, regression procedures, and Sobel’s Z-test. The mediation effect on the relationship between the independent and dependent variables was ascertained by path analysis (Structural Equation Modelling, or SEM) and the Medgraph Sobel’s Z-test.
 Findings: Results revealed a high descriptive level of job satisfaction and employee attrition and a very high descriptive level of stress management competency. It was found that job satisfaction and employee attrition, job satisfaction and stress management competency, and stress management competency and employee attrition are significantly related. The results revealed that stress management competency partially mediated the relationship between job satisfaction and employee attrition.
 Implications to Theory, Practice and Policy: Upskilling programs improve employees’ skills and knowledge, making them valuable assets to the organization. Employees may invest in both hard skills and soft skills. Organizations may also continue to recognize the accomplishments and achievements of their employees no matter how small or big they are because being recognized at work will boost employees' morale, which will also lead to efficiency and productivity. The concept of Diversity, Equity, and Inclusion (DEI) should continue to be practiced for long-term solutions to discrimination issues. Organizations, through their HRM, may continue formulating holistic programs and schemes that promote employees' physical and mental health, foster a positive working environment, a harmonious relationship, competitive salary, and benefits packages, and strengthen retention programs.

ORGANIZATIONAL CAPITAL AND EMPLOYEES’ COUNTERPRODUCTIVE WORK BEHAVIOUR IN THE NIGERIAN PUBLIC HEALTH SECTOR

This study was carried out with the view to assessing the impact of organizational capital on employees’ counterproductive work behaviour among some public healthcare organizations in Nigeria using Bayelsa state as a reference point. The study used a sample of two hundred and forty-three (243) employees of the selected organizations and data obtained were analyzed using both descriptive and inferential statistical tools. Specifically, the regression results indicated an insignificant but positive influence of organization capital on employees’ counterproductive work behaviour in public healthcare organizations. On the basis of the findings, it was recommended among others that organizations should regularly assess and monitor employee behaviour including counterproductive work behaviour via appropriate performance management systems and employee feedback mechanisms; this would allow organizations to identify early warning signs and take proactive measures to address any emerging issues.
 Keywords: Human Capital, Intellectual Capital, Public Health, Stress Facilitation Theory, Structural Capital, Work Overload.

How Do Arable Crop Farmers’ Adapt to Climate Change? New Evidence from Nigeria

In Nigeria, climate change is not a new phenomenon and arable crop production is vulnerable to climate change. Arable crop farmers have always responded to climate change with local strategies believed to be climate-smart. Arable crop farmers' knowledge of climate change is an important step in understanding any action to be taken to reduce its effect. However, empirical studies on the link between climate change and crop farmers’ adaptation strategies are still relatively scanty in the area. This presents a dearth in research. Therefore, our paper examined how arable crop farmers adapt to climate change using cross-sectional data obtained through a structured focused group discussion and questionnaire from 120 arable farmers across critical farming communities in Imo State, Nigeria. We utilized multistage and purposive sampling procedure in the selection of arable crop farmers. The reason we utilized purposive sampling procedure was to select areas with high intensity of arable crop farmers and farming. Data collected was analyzed using descriptive statistical tools and mean (x̄) score analysis. Our result shows that the mean age was 42.00 years. Greater proportions (73.00%) were female. The average farm size was 1.45 hectares. Vegetables (100.00%), maize (99.17%), cassava (98.33%) and rice (96.67%) were among the crops produced in the area. The result confirmed the incidence of climate change in the area and farmers perceived rightly the direction of the change, which includes declining crop yields (x̄ = 3.00; σ = 0.50), increased in new pests and diseases infestation (x̄= 2.88; σ = 0.58); unstable decrease and increase in temperature and rainfall (x̄=3.63, σ = 0.83) among others. Our study further shows that the major climate change adaptation measures farmers practiced were diversification of livelihood (99.17%) and changing planting/harvesting dates (97.50%). Farmers identified inadequate information (99.17) and inadequate climate change adaptation fund (98.33%) among others as the barriers they faced in adapting to climate change in the area. We recommend that, since arable crop farmers are members of cooperatives, they are encouraged to take advantage of their strength to collectively project a common demand in obtaining funds and other necessary inputs in adapting to climate change in the area. Finally, our study also suggests that the agricultural extension service system should be strengthened so as to provide farmers with stable and right early warning signs which will be critical in minimizing risks of climatic threats in the area.

Applications of Correlation Analysis in Environmental Problems

Objective: The aim of this work is to show the application of the Correlation Coefficient (Pearson, Spearman) to environmental problems. Theoretical framework: Although the concepts of correlation and regression are intimately related, they are nevertheless different. Correlation may be described as the degree of association between two variables, whereas regression expresses the form of the relationship between specified values of one (the independent, exogenous, explanatory, regressor, carrier or predictor) variable and the means of all corresponding values of the second (the dependent, outcome, response variable, the variable being explained) variable (Asuero et al., 2006). Method: Data was taken from 2 case studies in the environmental area and both were analyzed, the first with Pearson's Correlation Coefficient and the second with Spearman's Correlation Coefficient. Results and conclusion: It was determined that the samples had high Pearson's Correlation Coefficient values in both cases, which showed a very high correlation in both cases. The use of both types of Correlation Coefficient proved satisfactory in both cases. Implications of the research: The use cases of the Correlation Coefficient in the environmental area are multiplying in the scientific literature and are proving to be highly effective in showing the correlation between environmental variables. Originality/value: Despite being a well-known statistical tool, the Correlation Coefficient is widely used and can bring innovations in its application in cases of environmental variables.

Diversity and conservation status of herbal formulations used to treat different diseases in a semi-arid to sub-humid subtropical region

IntroductionThe current research aimed to discover the diversity and conservation status of medicinal plants used in herbal formulations to treat different diseases in Shakardara and adjacent areas, of Khyber Pakhtunkhwa, Pakistan. MethodsData were collected using semi-structured questionnaires about the preparation of monoherbal and polyherbal recipes that were used locally. Fidelity level, use value index, preference ranking method, and rapid vulnerability assessment were used for data interpretation. Relevant statistical tools (ANOVA and SPSS software) were used for data analysis. ResultsA total of 74 medicinal plants from 39 families were recorded that were used in the preparation of monoherbal and polyherbal formulation. In the study area, 146 recipes were used, of which 101 were monoherbal and 45 were polyherbal. Seeds were the most usable part of plants (28%), followed by fruits (23%) and leaves (21%). The highest informant consensus factor (1.00) was recorded for nail protection and growth, while the lowest (0.83) for wound healing. Withania coagulans Dunal was reported with the highest fidelity level and Peganum harmala L. was the most vulnerable species in the study area, with the highest threat score. ConclusionsConserving the knowledge and resources associated with the herbal remedies is essential for both human health and ecological balance. Monoherbal and polyherbal formulations of medicinal plants highlight the potential of traditional herbal remedies as valuable sources of alternative medicine. Further research in this field is crucial to explore the therapeutic potential and ensure the safe utilization of these natural remedies in modern healthcare.

THE EFFECT OF INFLUENCER MARKETING, VIRAL MARKETING AND CUSTOMER ENGAGEMENT ON PURCHASE INTENTION AT BLOODS STORE IN PURWOKERTO

This research investigates the multifaceted influence of contemporary marketing methodologies, namely influencer marketing, viral marketing, and customer engagement, on consumers' purchase intentions. This research used SmartPLS statistical analysis tool version 3.0. This research uses an online questionnaire with a total of 150 respondent from students of the Faculty of Economics and Business at Jenderal Soedirman University, University of Muhammadiyah Purwokerto, and State Islamic University Prof. KH. Saifuddin Zuhri Purwokerto that have purchase intention in Blood Store Purwokerto. Based on the findings of this research, it shows that influencer marketing, viral marketing, and customer engagement has a positive and significant impact on the purchase intention. By understanding the synergistic effects of these marketing approaches, businesses can strategically tailor their campaigns to optimize customer engagement and enhance purchase intentions, ultimately fostering greater success in today's competitive market landscape.This research investigates the multifaceted influence of contemporary marketing methodologies, namely influencer marketing, viral marketing, and customer engagement, on consumers' purchase intentions. This research used SmartPLS statistical analysis tool version 3.0. This research uses an online questionnaire with a total of 150 respondent from students of the Faculty of Economics and Business at Jenderal Soedirman University, University of Muhammadiyah Purwokerto, and State Islamic University Prof. KH. Saifuddin Zuhri Purwokerto that have purchase intention in Blood Store Purwokerto. Based on the findings of this research, it shows that influencer marketing, viral marketing, and customer engagement has a positive and significant impact on the purchase intention. By understanding the synergistic effects of these marketing approaches, businesses can strategically tailor their campaigns to optimize customer engagement and enhance purchase intentions, ultimately fostering greater success in today's competitive market landscape.

Student Perceptions of Emerging Virtual Teaching in Business Management Fields

In recent years, virtualization has been present in educational institutions, both in teaching-learning processes and in management and research, using the Internet to facilitate communication, document consultation and the virtual modality of courses, among others. This is why today the use of information technologies (ICT) is essential to facilitate the teaching process for teachers and the learning process for students. The objective of this study is to know about the perception of the students and the strategies implemented in the University Center of Economic-Administrative Sciences of the University of Guadalajara, to adapt the teaching and learning due to the contingency of COVID-19. The methodology is empirical and the data were obtained through interviews and the application of a questionnaire whose results were analyzed with statistical tools. The results show that students improved their autonomous learning, that the use of digital tools allows teachers to better explain the concepts, and that it is difficult to do teamwork and personal interaction but it is necessary.
 
 Received: 6 October 2023 / Accepted: 25 January 2024 / Published: 5 March 2024

Dance of Data in Pedagogical Research

This conference paper concentrates on the exploration of the interplay between statistics, probability distributions, t-tests, and the utilisation of the R language in pedagogical research. Statistics play a vital role in collecting, analysing, and interpreting data in educational research. The t-test, as a fundamental statistical tool, enables researchers to assess the significance of differences between groups, a common requirement in pedagogical studies. The integration of the R language, a powerful and flexible statistical computing tool, empowers researchers to conduct complex analyses efficiently. It acts as a bridge between statistical theory and practice, enabling the application of statistical methods to real-world educational data. This paper sheds light on the systematic approach to employing these elements, emphasising their practical importance in pedagogical research.

A Survey-Based Analysis of the Extent of Aluminium Involvement in our Lives for Risk Assessment

Despite being a non-essential metal in the body, we acquire aluminium via various sources such as aluminium cookware, foil, medicines, cosmetics, food, water, and aluminium-industries. Though it can be eliminated from our body, the excess and cumulative effect can’t be ignored. Aluminium load above the threshold causes several diseases like Alzheimer’s, osteomalacia, anaemia, and cancer. Hence, the current study was designed to explore the frequency of aluminium usage in various forms in the Indian population of northwest rural and urban regions of Maharashtra and investigate any preferential difference in aluminium usage with occupation, education, income, and family structure. It is a correlational study designed to check the extent of aluminium involvement in their lives and their perception of awareness. A non-random sampling method using social media was utilized for data collection, and data were analyzed using a statistical tool, Jamovi. A survey-based analysis of the responses to a pre-designed questionnaire was done. The prominent factor contributing to the aluminium load was found to be the aluminium vessel used in our kitchen. Boiling, storing, and baking edible items facilitate its leaching into food to toxic levels. Further analysis revealed a significant correlation of financial and educational status with aluminium usage. Reducing aluminium vessel usage for cooking can significantly reduce aluminium load in our bodies. However, we still need to be vigilant about the aluminium load which the other products are imparting upon us. Hence, awareness and exploring the alternatives are the only options to keep a check on the aluminium load.

The Effect Of Media Composition On The Growth Of Angsana (Pterocarpus Indicus)

The purpose of this research was to find out the Influence of the Composite of the Planting Media on the Growth of Angsana Plant and the composition of a good plant media for Angsana plantation. This research uses a single Design (DK) factor, with a medium dose treatment of M0 = Topsoil Each Polybag, M1 = Media 100 Gram Each Polybag, M2 = Media 200 Gram Each Polybag, M3 = Media 300 Gram Each Polybag. As a result, it will continue to be analyzed using the DMRT (Duncan Multiply Class Test) tasks 95% with the application of Statistics tools for Agriculture Research. The length of plant observation, for treatment with less control in each unit with a value of (A0) of 19.33cm, has no significant influence on the treatment of each unit. In addition to treatment (A1) 10 Treatment by (A3) 100.33cm and (A3) 40.33cm had a significant influence on treatment (A0) 19.33cm. of treatment A1, A3 and A2 showed that the influence of organic breastfeeding or animal waste on the supply of Angsana plants increased in length or height in each unit.

A Study on the Shrinkage and Compressive Strength of GGBFS and Metakaolin Base Geopolymer under Different NaOH Concentrations.

Geopolymers (GPs) are gaining prominence due to their low carbon emissions and sustainable attributes. However, one challenge with GPs, particularly those made with ground granulated blast furnace slag (GGBFS), is their significant shrinkage during the geopolymerization process, limiting its practical applicability. This study focuses on how the substitution ratio of metakaolin (MK) and the concentration of sodium hydroxide (NaOH) in the activator can influence the shrinkage and strength of a GGBFS-based GP. The experimental approach employed a 3 × 3 parameter matrix, which varied MK substitution ratios (0%, 50%, and 100%) and adjusted the NaOH concentration (6 M, 10 M, and 14 M). The results revealed that increasing MK substitution, particularly with 6 M NaOH activation, reduced the GP shrinkage but also diminished compressive strength, requiring higher NaOH concentrations for strength improvement. Statistical tools, including analysis of variance (ANOVA) and second-order response surface methodology (RSM), were employed for analysis. ANOVA results indicated the significant impacts of both the MK content and NaOH concentration on compressive strength, with no observable interaction. However, the shrinkage exhibited a clear interaction between MK content and NaOH concentration. The RSM model accurately predicted compressive strength and shrinkage, demonstrating a high predictive accuracy, for which the coefficients of determination (R2) were 0.99 and 0.98, respectively. The model provides a reliable method for determining the necessary compressive strength and shrinkage for GGBFS-based GP based on MK substitution and NaOH concentration. Within the optimization range, the RSM model compared with experimental results showed a 6.04% error in compressive strength and 0.77% error in shrinkage for one interpolated parameter set. This study establishes an optimized parameter range ensuring a GP performance that is comparable to or surpassing OPC, with a parameter set achieving a compressive strength of 34.9 MPa and shrinkage of 0.287% at 28 days.

Best Morpho-Physiological Parameters to Characterize Seed-Potato Plant Growth under Aeroponics: A Pilot Study

Best Morpho-Physiological Parameters to Characterize Seed-Potato Plant Growth under Aeroponics: A Pilot Study

An efficient metamodel to downscale total water level in open beaches

A hybrid methodology is described to obtain the wave set-up and infragravity wave level components for estimating total water level (TWL) in coastal areas, taking into account the surf zone hydrodynamics involved. By combining statistical tools and numerical methods, high-resolution spatial distributions of wave height and water level components are calculated efficiently and seamlessly. The proposed methodology is tested and numerically validated on La Salvé beach (Cantabria, Spain), showing a robust performance for diverse scenarios. The resulting TWL can efficiently evaluate coastal hazards in forecast and hindcast mode, having strong potential as a guideline for coastal engineers, managers and emergency planners in the elaboration of adaptation and mitigation strategies. As an application of the metamodel to these coastal management tasks, significant past storm events have been reconstructed, and their associated TWL-driven coastal flooding hazard has been analyzed using a impact rank scale.