Statistical Tools Research Articles

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.

Effect of Tax Revenue and Foreign Grants on Government Activities: A Study in Nepalese Perspective

This study aims to examine the impact of previous years’ government expenditure, tax revenue, and foreign grants on determining Nepal's government activities or expenditures. The secondary data from used in the analysis. It includes 48 data points from 1974/75 to 2021/22, collected from the publication of Nepal Rastra Bank and economic surveys of Nepal. The descriptive and exploratory research designs are used in this study. Some statistical and econometric tools like descriptive statistics, Kolmogorov-Smirnov test, multiple regression analysis, analysis of variance (ANOVA), and residual analysis are used in this study. The previous expenditure determines the present government activities. Tax revenue, foreign grants, and previous years’ government expenditures are individually and jointly significant in determining the government expenditure. One unit increase in tax revenue and foreign grants resulted in a 0.177 and 0.046 unit increase in government expenditure in Nepal, respectively. 86.5 percent variation in government activities is determined by the previous year's government expenditure, tax revenue, and foreign grants. The positive impact of tax revenue is more than foreign grants on spending government activities. So, the policymakers must prioritize measures that increase domestic tax revenue.

On the gamma radiation response of commercially available 3D printing materials for medical dosimetry

3D printing technology has rapidly spread for decades, allowing the fabrication of medical implants and human phantoms and revolutionizing healthcare. The objective of this study is to evaluate some radiological properties of commercially available 3D printing materials as potential tissue mimicking materials. Among fifteen materials, we compared their properties with nine human tissues. In all materials and tissues, exposure and energy absorption buildup factors were calculated for photon energies between 0.015 and 15 MeV and penetration depths up to 40 mean free path. Furthermore, the Geant4 Monte Carlo toolkit (version 10.5) was used to simulate their percentage depth dose distributions. In addition, equivalent atomic numbers, effective atomic numbers, attenuation coefficients, and CT numbers have been examined. All parameters were considered in calculating the average relative error (σ), which was used as a statistical comparison tool. With σ between 6 and 7, we found that Polylactic Acid (PLA) was capable of simulating eye lenses, blood, soft tissue, lung, muscle, and brain tissues. Moreover, Polymethacrylic Acid (PMAA) material has a σ value of 4 when modeling adipose and breast tissues, respectively. Aside from that, variations in 3D printing materials’ infilling percentage can affect their CT numbers. We therefore suggest the PLA for mimicking soft tissue, muscle, brain, eye lens, lung and blood tissues, with an infill of between 92.7 and 94.3 percent. We also suggest an 89 percent infill when simulating breast tissue. Furthermore, with a 96.7 percent infill, the PMAA faithfully replicates adipose tissue. Additionally, we found that a 59 percent infill of Fe-PLA material is comparable to cortical bone. Due to the benefits of creating individualized medical phantoms and equipment, the results might be seen as an added value for both patients and clinicians.

An improved low‐carbon intelligent agriculture system with energy optimization principles using wireless IoT environment

AbstractA low‐carbon agricultural plan and intelligent agriculture control system are designed and completed with a green economy to foster the significant expansion of green resources and environmental assets. This research employs a fixed‐effect panel model to examine the farming cumulative energy savings in 11 cities and regions along the Yamuna Tributary Commercial Region, focusing on both static and dynamic factors. The directional linear equation and the Malmquist–Luenberger (ML) indicator are the key analytical tools. Unlike conventional techniques, regression analysis using cross‐sectional data is the primary tributary. Research has found that a 5.9% decrease in the literacy rate of the working force had a large impact on farming energy efficiency and that for each 1% rise in crop losses, farm energy efficiency would decrease by 0.487%. In addition to mitigating the detrimental effects of industrial design and mechanization on agricultural output, this effort aids in the advancement of smart city design. This activity paves the way for cutting‐edge technology by encouraging people to move to cities, educating the workforce, and giving money to the agricultural sector. The ability of proposed model gives the smart agriculture system with intelligent control principles and energy optimization principles in the deployed wireless‐IoT platform. On this research problem, this paper contributes to new knowledge by approaching agricultural energy efficiency from a green economy perspective, conducting regression analyses of panel data on the most important influencing factors using the advanced statistical analysis tool Eviews, and then drawing the conclusion from the evaluation of metrics that affect farming energy efficiency in our nation. Enhancing productivity while also fostering long‐term growth in the agricultural ecosystem is crucial. It contributes for smart and green technologies adaptation in agriculture filed.

Evaluation of behavioral variance/covariance explained by the neuroimaging data through a pattern-based regression.

Neuroimaging data have been widely used to understand the neural bases of human behaviors. However, most studies were either based on a few predefined regions of interest or only able to reveal limited vital regions, hence not providing an overarching description of the relationship between neuroimaging and behaviors. Here, we proposed a voxel-based pattern regression that not only could investigate the overall brain-associated variance (BAV) for a given behavioral measure but could also evaluate the shared neural bases between different behaviors across multiple neuroimaging data. The proposed method demonstrated consistently high reliability and accuracy through comprehensive simulations. We further implemented this approach on real data of adolescents (IMAGEN project, n = 2089) and adults (HCP project, n = 808) to investigate brain-based variances of multiple behavioral measures, for instance, cognitive behaviors, substance use, and psychiatric disorders. Notably, intelligence-related scores showed similar high BAVs with the gray matter volume across both datasets. Further, our approach allows us to reveal the latent brain-based correlation across multiple behavioral measures, which are challenging to obtain otherwise. For instance, we observed a shared brain architecture underlying depression and externalizing problems in adolescents, while the symptom comorbidity may only emerge later in adults. Overall, our approach will provide an important statistical tool for understanding human behaviors using neuroimaging data.

An approach to the analysis of deforestation in Colombia, applications of physical tools

Deforestation, a global challenge with significant environmental and social impacts, raises pressing concerns for the sustainability of the planet, especially in Colombia. This phenomenon, particularly relevant in the Colombian context where biodiversity and national identity are intrinsically linked, has undergone a dramatic transformation in recent decades due to the expansion of anthropogenic activities. This article clarifies the current state of the problem, discusses the efforts undertaken by the Office of the Procuraduria General de la Nación colombiana, and proposes an innovative approach by integrating statistical tools, formalism inherent to statistical mechanics, and geographical features. Leveraging quarterly data issued by the Instituto de Hidrología, Meteorología y Estudios Ambientales, such as early deforestation alerts, the study will outline a methodology to discern patterns and behaviors.

Environmental – Solar thermal effects a long-term on the efficiency of amorphous climate-resilient mortar using a central composite design application

The objective of this investigation is to evaluate the durability of dune sand mortar containing display e-glass waste (DEGW) in severe Saharan environments, chemical attacks, or other factors that can cause cementitious materials to deteriorate at long- term. The aim is to use DEGW powder as a partial replacement for dune sand in various mortar mixtures and assess the performance of hardened mortar in terms of ultrasonic pulse velocity, dynamic elasticity modulus, compressive strength, and flexural strength and sportivity. The study also examines the influence of the curing period and different climatic conditions in curing environments, such as those in Algeria's Sahara region. The Response Surface Methodology (RSM) was used to adjust the e-waste glassy mortar, with the statistical tool Central Composite Design (CCD) approach. The hydration of cement compounds was monitored using differential thermal analysis (DTA), thermogravimetric analysis (TGA), Differential Scanning Calorimetry (DSC), and X-ray diffraction (XRD). The DEGW was replaced in 5% increments from 0% to 20%. The results showed that the glassy dune sand mortar exhibited the highest properties at 20% incorporation after 365 days of severe climatic conditions. The feasibility of the proposed quadratic model was recommended for the five responses by RSM, in which the coefficient of determination (R2) ranges from 0.93 to 0.97, showing the model’s high significance. For structural display e-glassy dune sand mortar, display glass E-waste can replace 20% of dune sand, which improves all durability and environmental sustainability. Furthermore, the DSC, TGA / DTA results and XRD analysis showed that the < 0.08 mm class exhibited good pozzolanic behaviour, and the specimens significantly improved as curing periods increased.

Core Literacy of Physical Education Discipline and The Sports Performance of Selected Sports Majors in China

This study aimed to determine the assessment of the current situation of sports discipline and core literacy of students majoring in sports specialty in colleges and universities in China, and to find out the challenges and obstacles that hinder their participation in sports and training. It utilized the descriptive comparative -correlational research design in the conduct of the study. To ensure the valid and systematic presentation, analysis and interpretation of the data, the following statistical tools were obtained: frequency count and percentage, weighted mean, ranking, P value and t-test/ and Pearson’s r Correlation Analysis. Results of the study revealed that Sportsmanship, sports practice, and health promotion have all been assessed as highly consistent with Core Literacy in Physical Education. There is a favorable ecosystem surrounding sports education, with active participation and support from communities and institutions. The highly significant correlations observed between sportsmanship, sports practices, and health promotion with sports performances and sports involvement and support highlight the interconnectedness of these elements within the discipline. The Core Literacy of Physical Education encompasses a wide range of components, including physical qualities, health improvement, values development, teamwork, leadership, communication skills, cultural literacy, creativity, and emotional intelligence. These components collectively contribute to the holistic development of individuals and communities.

Association of salted tea (noon chai), Helicobacter pylori infection and gastric carcinoma

Background: Gastric cancer remains the second leading cause of cancer-related deaths worldwide. Various dietary and environmental factors have been implicated in the pathogenesis of gastric cancer. Helicobacter pylori has strong association with peptic ulcer disease and gastric cancer. Methods: This study was conducted in department of general and minimal invasive surgery SKIMS Srinagar, from May 2019 to April 2022 comprising of 50 patients. All the patients were studied prospectively using set of questionnaires about the quantity and quality of salted tea. Final inferences were drawn after analysing the data using various statistical tools. Results: The most common age group was &gt;60 years of age with male preponderance. Majority of patients had no comorbidity. About 50% of the patients were smokers. The most common histology found was intestinal type. 20% patients had proximal (cardia) tumor and 80% had distal location. Only 14% of the patients came positive for intra-operative H. pylori testing. Among the H. pylori positive patients, 14.3% were &lt;40 years of age and 85.7% were &gt;40 years of age. The most common histological grade found in H. pylori positive patients was poorly differentiated with signet ring cell type. About 88% of all the patients had a history of Noon chai intake with 14% positive and 86% negative for H. Pylori. Conclusions: There is a positive relation between Noon chai and gastric carcinoma and an inverse relation between ca stomach and presence of H. pylori intraoperatively at the time of surgical intervention.

Teachers’ Research Competence and Engagement: Basis for Research Development Plan

Teachers’ research and competence posited complementary synergy theorizing that teachers with higher research competence are engaged in research pursuits relevant to professional growth within the context of education. This research addressed six key objectives by profiling respondents, assessing teachers’ competence on framing questions and data collection, identifying literature and theoretical knowledge, and analyzing and presenting research data, and research engagement levels on motivation to write research, and difficulty in conducting research, determining significant relationships between competence and engagement, exploring the correlation between engagement and respondents’ profiles, and designing a research development plan. Employing an adapted survey questionnaire using a universal sampling method, 391 teachers across the two districts in the Division of El Salvador City were surveyed during the School Year 2023–2024. Statistical tools such as means, frequency, standard deviation, Pearson-r, and triangulations were applied for data analysis. Findings indicated a positive correlation between teachers’ research competence and engagement. A significant relationship was identified between engagement and moderating variables like related training and position. Despite the teachers being competent and engaged, their research work was hindered by the number of coordinatorships they handled. It is important to emphasize the research competence and engagement for educational improvement as it illuminates the current state of teachers’ research skills and lays the groundwork for a targeted Research Development Plan.