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Research & Reviews : Journal of Statistics
Number of Followers: 4

This is an Open Access Journal

Open Access journal
ISSN (Print) 2348-7909 - ISSN (Online) 2278-2273
Published by STM Journals

[67 journals]

A statistical analysis of Indian National Florence Nightingale Nurses
Awards, 1973-2023
- Authors: Susanta Koley
  Pages: 18 - 34
  Abstract: This study is an attempt to analyses 614 National Florence Nightingale Nurses Awards for the period of 1973-2023. It analyses year-and gender-wise number of awardees or awards including posthumous and off-service awards. This study has also been able to find number of recipients or awards according to state, category and affiliation. The result shows that the number of awards has gradually increased from the beginning and mostly given from 2008 to 2021. It has declined in the years 2022 and 2023 to less than half of the previous years. It has peaked during the quinquennium 2018-2022. The largest number of awards has conferred to 554 female nursing professionals, whereas 41 to male; 4 to death and 15 to retired personnel. A state-wise rank list highlights Delhi as the highest award (i.e., 54 awards) winner state in India and nursing personnel of Delhi still retain excellency in patient care services. In case of award distribution according to category, out of 439 awards, nurse and sister group (including ANM, GNM, other nurses, sisters, etc.) has received the highest awards (i.e., 342), followed by nursing administrators (70 awards), and nursing educators & researchers (27 awards). As per affiliation, during last 12 years, nursing professionals of Dr. Ram Manohar Lohia Hospital & PGIMER, New Delhi have won the largest number of awards i.e., 8; the second is Sher-I-Kashmir Institute of Medical Sciences, Jammu & Kashmir having 7 awards, and National Institute of Mental Health and Neuro Sciences (NIMHANS), Karnataka, is ranked third position receiving 6 awards.
  PubDate: 2024-07-06
  DOI: 10.37591/rrjost.v12i3.3893
  Issue No: Vol. 12, No. 3 (2024)
Advance in Spatial Statistics for Environmental Data Analysis
- Authors: Neha Sahu
  Pages: 35 - 39
  Abstract: Recent advancements in spatial statistics have significantly enhanced the analysis of environmental data, addressing complex spatial dependencies and offering robust methodologies for environmental monitoring, modeling, and decision-making. This abstract highlights key developments in the field, emphasizing their applications and impact. Geostatistical Methods, Improved geostatistical techniques, such as kriging and co-kriging, provide more accurate predictions of environmental variables by incorporating spatial correlation structures. Advanced kriging variants, including Bayesian kriging and machine learning-enhanced kriging, offer increased flexibility and precision. These models account for spatial autocorrelation and heterogeneity, enabling better understanding of the relationship between environmental factors and outcomes. This approach improves the estimation of environmental processes and the quantification of uncertainty, making it a powerful tool for complex environmental data. Environmental Monitoring, Enhanced spatial statistical methods improve the monitoring of air and water quality, climate change impacts, and biodiversity, aiding in the early detection of environmental hazards. Resource Management, Spatial statistics support the efficient management of natural resources, such as forests, water bodies, and agricultural lands, by providing accurate spatial predictions and assessments. Urban Planning, The application of spatial statistics in urban planning helps in assessing the environmental impact of urbanization, optimizing land use, and mitigating pollution and heat island effects. Advances in spatial statistics are pivotal for tackling environmental challenges in the era of big data. By leveraging these sophisticated techniques, researchers and policymakers can achieve more accurate, reliable, and comprehensive environmental data analyses, leading to informed decision-making and sustainable management of environmental resources.
  PubDate: 2024-07-27
  DOI: 10.37591/rrjost.v12i3.3892
  Issue No: Vol. 12, No. 3 (2024)
Grey relational fractional programming and cross-evaluating method for
multi-attribute decision making problem in spherical fuzzy setting
- Authors: Gol Kim, Ri Suk Yun
  Pages: 40 - 52
  Abstract: To apply the spherical fuzzy sets(SFSs) for multiple attribute decision making (MCDM) problems have the more realistic significance, because of the assessment data specified by experts are mostly fuzzy and uncertain, the uncertainty and vagueness, ambiguity and subjectivity of the information in an intricate decision making environment, In this paper, a method to acquire attribute weights of interval number form by using the maximization method of the grey relational relative closeness degree in SFSs circumstance is proposed. To obtain the upper bound and lower bound of relative closeness degree, two fractional programming models are suggested. Possibility matrix is obtained by using the possibility degree of interval numbers, the optimal membership degrees from possibility matrix is obtained. The decision making method by the optimal membership degrees is proposed. To demonstrate the effectiveness and feasibility of proposed method an illustrate example is presented.
  PubDate: 2024-08-09
  DOI: 10.37591/rrjost.v12i3.3814
  Issue No: Vol. 12, No. 3 (2024)
Testing for equalities of several multinomial distributions
- Authors: Patel S.R.
  Abstract: In this article we have studied the testing of parameters of several multinomial distributions. The necessary conditional distribution of complete sufficient statistic of the parameter of interest is obtained by conditioning the complete sufficient statistics of nuisance parameter to be held fixed .Using this conditional distribution we have derived uniformly most powerful unbiased (UMPU) test for testing the hypothesis (i)Equality of two independent multinomial distributions and (ii) testing one of the parameters of multinomial distribution is equal to or larger than the corresponding parameters of another independent multinomial distribution. Asymptotic test have been derived for testing (i) and (ii).The application of these tests have been done to associate class in data mining.
  PubDate: 2023-12-30
  DOI: 10.37591/rrjost.v12i3.3661
  Issue No: Vol. 12, No. 3 (2023)
Mathematical Analysis of prey-predator model
- Authors: A. V. PapaRao, G. A. L. Satyavathi, K. Sobhan Babu
  Abstract: In this paper we considered a model with a prey and predator involve holling type -II functional response. The predator species is not only dependent on prey species but also have alternative food source. The mathematical model is characterized by the couple of differential equations. The model is well posed and possess positive solutions. The system is bounded and shows the property of permeance. The possible equilibrium points are identified. At each point local stability analysis is studied. The global stability analysis is also addressed using Lyapunov’s function approach. The sufficient condition is derived to prove that the system does not admit any periodic oscillations using Bendixen-Dulac criteria. Finally, numerical simulation is performed in support of analytical results.
  PubDate: 2023-12-22
  DOI: 10.37591/rrjost.v12i3.3721
  Issue No: Vol. 12, No. 3 (2023)
An Inferential Statistical Analysis of Quantity Surveyors’ Awareness of
Organisational Barriers to Risk Management Practices on Construction
Projects
- Authors: Alolote Ibim Amadi
  Abstract: This study was carried out to statistically evaluate Quantity Surveyors’ level of awareness concerning risk management practices and the perceived organizational barriers to their implementation in construction projects. Demographic data was collated to test the hypothesis that there is a significant relationship between the level of awareness of risk management practices and the type of Quantity Surveying organization as well as their academic qualification. Using the survey research strategy, questionnaires were administered to Quantity Surveyors in different types of organisations including public parastatals, private practice, consultancy, and academia, in Port-Harcourt, Nigeria. The statistical validity of the questionnaire instrument was established via piloting, while Reliability was established by applying using non-parametric test of significance. Different sets of inferential statistics were used to analyze the data from the questionnaires, including the Chi-square test for the independence of two categorical variables at a 0.05 significance level and relative importance indices. For the Chi-square test, the data was first cross-tabulated according to the type of organisation and then based on academic qualifications. The statistical analysis revealed that the ꭓ2 (calculated) was less than the ꭓ2 (critical) for the former and not for the latter. The outcome of the statistical analysis therefore upheld the hypothesis, that there is a significant relationship between the type of organisation and quantity surveyors’ level of awareness of risk management. It can thus be inferred that the type of organization significantly impacts the level of awareness of quantity surveyors regarding risk management and not their level of academic qualification. The ranking of the relative importance indices showed that the primary organizational barrier to the implementation of risk management was a lack of appreciation of the benefits associated with risk management practices. It is recommended that more workshops and seminars should be structured at the organisational level for more enlightenment on the need for risk management practices on construction projects.
  PubDate: 2023-11-24
  DOI: 10.37591/rrjost.v12i2.3749
  Issue No: Vol. 12, No. 2 (2023)

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