Nepalese Journal of Statistics 2023-12-29T09:58:40+00:00 Srijan Lal Shrestha, PhD Open Journal Systems <p>Nepalese Journal of Statistics is the official journal of the Central Department of Statistics, Tribhuvan University, Kirtipur, Nepal.</p> Modeling and Forecasting of Spinach Production in Bangladesh 2023-12-25T01:47:01+00:00 Keya Rani Das Mashrat Jahan Linnet Riya Barman Preetilata Burman <p><strong>Correction: </strong>On 03/01/2024 the PDF was replaced because of an error discovered in Table 9. In Table 9, ARIMA (1, 1, 0) replaces ARIMA (0, 1, 2).</p> <p><strong>Background:</strong> In Bangladesh, spinach (<em>Spinachia oleracea L.</em>) is most frequently known as "Palong shak" or Bengal Spinach. Spinach is one of the most prominent vegetable crops grown around the earth. It is a quick-growing annual plant that only lives for one year. Although spinach can be cultivated at any time throughout the year, Bangladesh's production of spinach on a per-unit basis is very low in comparison to that of other advanced nations.</p> <p><strong>Objective: </strong>This study explores the impacts of area, price, and weather parameter adaptability on the local production of spinach in Bangladesh employing annual data from time series covering 60 years.</p> <p><strong>Materials and Methods: </strong>This investigation seeks to comprehend the linear relationship between spinach production, commercial price, geographic location, and meteorological characteristics in Bangladesh by applying stepwise regression analysis to find the most suitable model of Spinach production. In order to evaluate how well the multiple linear regression model fits the data, several diagnostic charts were constructed using the R programming language. To forecast the Spinach production, an autoregressive integrated moving average (ARIMA) model was applied.</p> <p><strong>Results: </strong>According to the findings of the study, there was a positive correlation between spinach output and total harvest area under spinach cultivation. There is weak positive correlation between production and annual mean temperature and a weak negative correlation exists between production and annual mean rainfall. Also, production is perfectly positively correlated with price. Regression analysis revealed that the variables sales price and annual mean rainfall are the best predictors of spinach output. Every unit increase in the price of spinach is increases an additional 5.98 times the average of spinach being produced. An increase of 1 millimeter in annual mean rainfall (AMR) decreases 0.001 times spinach production while other predictors remain fixed. Also, ARIMA (1, 1, 0) with drift model forecasts for next fifteen years that the Spinach production is expected to increase considerably by 75000 tons.</p> <p><strong>Conclusion: </strong>Finally, the study found that farmers' perspective on spinach cultivation could potentially experience a positive upward shift which is expected to last for the next fifteen years.</p> 2023-12-29T00:00:00+00:00 Copyright (c) 2023 Central Department of Statistics, Tribhuvan University Factors Affecting Academic Performance of M. Sc. Level Students at Tribhuvan University 2023-12-25T02:14:17+00:00 Sudhir Tamang Shankar Prasad Khanal <p><strong>Background:</strong> Several factors contribute to a student's academic performance. Studies have examined the direct impact of student-related factors and the broader influence of social and economic factors.</p> <p><strong>Objective:</strong> To identify the important factors influencing the academic performance of Master's level students at the Institute of Science and Technology (IoST), Tribhuvan University (TU).</p> <p><strong>Materials and Methods: </strong>Primary data of 251 master’s level students was collected with a questionnaire adapted and developed from similar studies. The data was collected using convenience sampling. In addition to demographic and categorical questions, five-point Likert scale questions were also used. Data analysis involved fitting a multiple linear regression (MLR) with the identified significant independent variables. The goodness of fit of the model was evaluated to assess the accuracy and reliability of the final model in explaining variations in students' SGPA (Semester Grade Point Average).</p> <p><strong>Results:</strong> The study revealed that students' motivation, study habits, and communication skills significantly influenced their SGPA. Study habits showed a coefficient of 0.118 (p &lt; 0.001), indicating a positive and significant relationship with SGPA. Student motivation had a coefficient of 0.19 (p &lt; 0.001). Similarly, Higher levels of motivation were linked to improved SGPA outcomes. Communication skills exhibited a coefficient of 0.086 (p &lt; 0.001) at a 5% level of significance. All these factors had a positive coefficient which means students better on these factors on an average will tend to have better academic performance.</p> <p><strong>Conclusion:</strong> Study habits, motivation, and communication skills were found to have a significant effect on students’ SGPA. Therefore, we can conclude that at the master's level in IoST, TU, the primary determinants of students' SGPA are their characteristics such as their motivation, study habits, and communication skills.</p> 2023-12-29T00:00:00+00:00 Copyright (c) 2023 Central Department of Statistics, Tribhuvan University Status of Hypertension and its Determinants among Teachers in Tribhuvan University Campus, Kirtipur, Kathmandu 2023-12-25T02:23:08+00:00 Krishna Khadka Pravat Uprety <p><strong>Background</strong>: Hypertension, often known as high blood pressure, is a crucial public health issue and an essential topic of study because of its high prevalence and being a vital exposure to cardiovascular diseases and other health consequences. Therefore, being both a standalone disease and a precursor to non-communicable illnesses, hypertension poses a global health menace.</p> <p><strong>Objective</strong>: The study was conducted to investigate the status of hypertension and its associated risk factors among the teachers from Tribhuvan University Campus.</p> <p><strong>Materials and Methods</strong>:&nbsp; The cross-sectional research study involved 247 teachers from TU central campus using stratified random sampling and both descriptive and inferential statistical analytical methods. Multinomial logistic regression model was employed to investigate the relationship between several variables and hypertension levels.</p> <p><strong>Results:</strong> The fitted model, which had a classification accuracy of 67.2%, met the diagnostic test requirements for goodness of fit, multi-collinearity and minimal criteria of the model's use. Influential variables for pre-hypertension included interpersonal relationship, age group, gender, duration of service, smoking and physical activeness. For hypertension, significant variables encompassed job itself, interpersonal relationship, age group (45-50 years), gender, duration of service, smoking, tobacco use and physical activeness.</p> <p><strong>Conclusion: </strong>It was observed that 37.7% of the respondents had hypertensive status, 30.3% were surpassing normotensive and 32.0% were pre-hypertensive. Teachers’ hypertension status was discovered to be influenced by a variety of sociodemographic, behavioral, clinical, and stress variables. Concerned authorities must pay close attention to this issue.</p> 2023-12-29T00:00:00+00:00 Copyright (c) 2023 Central Department of Statistics, Tribhuvan University Comparative Study of Risk in General-Finance and Production-Service Categories of NEPSE Market 2023-12-25T02:57:56+00:00 Kiran Kumar Shrestha Rabindra Kayastha <p><strong>Background: </strong>The study of risk in investment in the stock market has become a popular area of research since last few decades. The inherent nature of risk that is associated with volatile behavior of stock prices as well as of returns of investment makes investors to think more than once before investing in stock markets. In this regard, this research is focused on comparison of risk associated with investment in General-Finance and Production-Service groups of the NEPSE market.</p> <p><strong>Objective: </strong>Primary objective of this research is to assess and compare risk present in the ‘General-Finance’ group and the ‘Production-Service’ group of the NEPSE market.</p> <p><strong>Materials and Methods: </strong>Different companies enlisted in the NEPSE stock market are categorized into ten groups. Some of the groups are related to direct financial activities and they are placed in the ‘General-Finance’ group. Other groups which are related to production and service activities are placed in the ‘Production-Service’ group. Daily means of NEPSE indices for these groups, available from official website of NEPSE are used to fit ARIMA model to the indices of ‘General-Finance’ and to ‘Production-Service’ groups. It is attempted to compare risks in these two groups with respect to the variance of error terms of the fitted models. Moreover, GARCH models are employed to describe conditional heteroscedasticity present in observations.</p> <p><strong>Results: </strong>It is observed that ARIMA (1, 1, 3) is the optimal model for daily indices of ‘General-Finance’ group with variance of errors terms observed to be 4636.1933. For the ‘Production-Service’ group the optimal model resulted is ARIMA (1, 1, 1) with variance of error terms being 1335.0058. Conditional heteroscedasticity and volatility clustering are observed to have GARCH (1, 1) model for both the groups.</p> <p><strong>Conclusion: </strong>After observing variance of error terms of optimal ARIMA models for ‘General-Finance’ and ‘Production-Service’ group and coefficients of GARCH models, it is concluded that ‘General-Finance’ group owes more risk in investment than that in ‘Production-Service’ group.</p> 2023-12-29T00:00:00+00:00 Copyright (c) 2023 Central Department of Statistics, Tribhuvan University Systematic Review on Factors Associated with Female Age at Marriage 2023-12-25T03:09:16+00:00 Ishwar Kumar Shrestha Shankar Prasad Khanal <p><strong>Background:</strong> Female age at marriage is one of the major indicators of population dynamics associated with age at which marriable couples are united and simultaneously acts of giving new childbirth with new family roles. Occurrence of marriage before the body being physically fit and mentally matured results in many adverse consequences. However, less attentions have been given to the variability of female age at marriage which can be influenced by different factors.</p> <p><strong>Objective:</strong> This review paper is an attempt to explore significant factors associated with female age at marriage, and to mark those factors as explained by model-based statistical effect size.</p> <p><strong>Materials and Methods:</strong> Following the PRISMA- Preferred Reporting Items for Systematic Review and Meta-Analysis guideline, three databases EMBASE, PubMed and Scopus were used to identify relevant articles combining key search terms using Boolean operations. From these databases, a total of 605 eligible articles originally published in English language till the date of 20 November, 2023 were identified. Applying the inclusion and exclusion criteria only 17 papers which had used statistical models were ascertained for final review.</p> <p><strong>Results:</strong> The effect size which was found significant at 0.05 level of significance explored that female’s education, place of residence, religion, caste/ethnicity, birth cohort, current age, female’s work status, type of occupation, wealth index, husband’s education are the major determinants, which are observed to be significantly associated with female age at marriage. </p> <p><strong>Conclusion: </strong>Female age at marriage is found to be varied from place to place, region to region and country to country. As the level of education increased, the possibility of acquiring early age at marriage has been reduced significantly. The demographic, socio-economic, gender and community factors played significant roles at the timing of females age at marriages. Moreover, female age at marriage has a considerable impact on fertility measures and population structure. Hence, policy relating to improving female age at marriage and its associated effective enforcement of law are required to meet the SDGs targets.</p> 2023-12-29T00:00:00+00:00 Copyright (c) 2023 Central Department of Statistics, Tribhuvan University Supplementary Materials: Modeling and Forecasting of Spinach Production in Bangladesh 2023-12-25T04:49:42+00:00 Keya Rani Das Keya Rani Das Mashrat Jahan Linnet Riya Barman Preetilata Burman <p>As mentioned in the manuscript.</p> 2023-12-29T00:00:00+00:00 Copyright (c) 2023 Central Department of Statistics, Tribhuvan University Supplementary Materials: Status of Hypertension and its Determinants among Teachers in Tribhuvan University Campus, Kirtipur, Kathmandu 2023-12-25T05:01:37+00:00 Krishna Khadka Pravat Uprety <p>As mentioned in the manuscript.</p> 2023-12-29T00:00:00+00:00 Copyright (c) 2023 Central Department of Statistics, Tribhuvan University