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PROBABILITIES AND MATH STATISTICS (113 journals)                     

Showing 1 - 98 of 98 Journals sorted alphabetically
Advances in Statistics     Open Access   (Followers: 9)
Afrika Statistika     Open Access   (Followers: 1)
American Journal of Applied Mathematics and Statistics     Open Access   (Followers: 11)
American Journal of Mathematics and Statistics     Open Access   (Followers: 9)
Annals of Data Science     Hybrid Journal   (Followers: 14)
Annual Review of Statistics and Its Application     Full-text available via subscription   (Followers: 7)
Applied Medical Informatics     Open Access   (Followers: 11)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 8)
Asian Journal of Probability and Statistics     Open Access  
Austrian Journal of Statistics     Open Access   (Followers: 4)
Biostatistics & Epidemiology     Hybrid Journal   (Followers: 4)
Cadernos do IME : Série Estatística     Open Access  
Calcutta Statistical Association Bulletin     Hybrid Journal  
Communications in Mathematics and Statistics     Hybrid Journal   (Followers: 4)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Communications in Statistics: Case Studies, Data Analysis and Applications     Hybrid Journal  
Comunicaciones en Estadística     Open Access  
Econometrics and Statistics     Hybrid Journal   (Followers: 1)
Forecasting     Open Access   (Followers: 1)
Foundations and Trends® in Optimization     Full-text available via subscription   (Followers: 3)
Frontiers in Applied Mathematics and Statistics     Open Access   (Followers: 1)
Game Theory     Open Access   (Followers: 2)
Geoinformatics & Geostatistics     Hybrid Journal   (Followers: 14)
Geomatics, Natural Hazards and Risk     Open Access   (Followers: 13)
Indonesian Journal of Applied Statistics     Open Access  
International Game Theory Review     Hybrid Journal   (Followers: 1)
International Journal of Advanced Statistics and IT&C for Economics and Life Sciences     Open Access  
International Journal of Advanced Statistics and Probability     Open Access   (Followers: 7)
International Journal of Algebra and Statistics     Open Access   (Followers: 3)
International Journal of Applied Mathematics and Statistics     Full-text available via subscription   (Followers: 3)
International Journal of Ecological Economics and Statistics     Full-text available via subscription   (Followers: 4)
International Journal of Energy and Statistics     Hybrid Journal   (Followers: 3)
International Journal of Game Theory     Hybrid Journal   (Followers: 3)
International Journal of Mathematics and Statistics     Full-text available via subscription   (Followers: 2)
International Journal of Multivariate Data Analysis     Hybrid Journal  
International Journal of Probability and Statistics     Open Access   (Followers: 4)
International Journal of Statistics & Economics     Full-text available via subscription   (Followers: 6)
International Journal of Statistics and Applications     Open Access   (Followers: 2)
International Journal of Statistics and Probability     Open Access   (Followers: 3)
International Journal of Statistics in Medical Research     Hybrid Journal   (Followers: 5)
International Journal of Testing     Hybrid Journal   (Followers: 1)
Iraqi Journal of Statistical Sciences     Open Access  
Japanese Journal of Statistics and Data Science     Hybrid Journal  
Journal of Biometrics & Biostatistics     Open Access   (Followers: 4)
Journal of Cost Analysis and Parametrics     Hybrid Journal   (Followers: 5)
Journal of Environmental Statistics     Open Access   (Followers: 4)
Journal of Game Theory     Open Access   (Followers: 1)
Journal of Mathematical Economics and Finance     Full-text available via subscription  
Journal of Mathematics and Statistics Studies     Open Access  
Journal of Modern Applied Statistical Methods     Open Access   (Followers: 1)
Journal of Official Statistics     Open Access   (Followers: 2)
Journal of Quantitative Economics     Hybrid Journal  
Journal of Social and Economic Statistics     Open Access  
Journal of Statistical Theory and Practice     Hybrid Journal   (Followers: 2)
Journal of Statistics and Data Science Education     Open Access   (Followers: 2)
Journal of Survey Statistics and Methodology     Hybrid Journal   (Followers: 4)
Journal of the Indian Society for Probability and Statistics     Full-text available via subscription  
Jurnal Biometrika dan Kependudukan     Open Access  
Jurnal Ekonomi Kuantitatif Terapan     Open Access  
Jurnal Sains Matematika dan Statistika     Open Access  
Lietuvos Statistikos Darbai     Open Access  
Mathematics and Statistics     Open Access   (Followers: 2)
Methods, Data, Analyses     Open Access   (Followers: 1)
METRON     Hybrid Journal   (Followers: 1)
Nepalese Journal of Statistics     Open Access  
North American Actuarial Journal     Hybrid Journal   (Followers: 1)
Open Journal of Statistics     Open Access   (Followers: 3)
Open Mathematics, Statistics and Probability Journal     Open Access  
Pakistan Journal of Statistics and Operation Research     Open Access   (Followers: 1)
Physica A: Statistical Mechanics and its Applications     Hybrid Journal   (Followers: 6)
Probability, Uncertainty and Quantitative Risk     Open Access   (Followers: 2)
Ratio Mathematica     Open Access  
Research & Reviews : Journal of Statistics     Open Access   (Followers: 3)
Revista Brasileira de Biometria     Open Access  
Revista Colombiana de Estadística     Open Access  
RMS : Research in Mathematics & Statistics     Open Access  
Romanian Statistical Review     Open Access  
Sankhya B - Applied and Interdisciplinary Statistics     Hybrid Journal  
SIAM Journal on Mathematics of Data Science     Hybrid Journal   (Followers: 1)
SIAM/ASA Journal on Uncertainty Quantification     Hybrid Journal   (Followers: 2)
Spatial Statistics     Hybrid Journal   (Followers: 2)
Sri Lankan Journal of Applied Statistics     Open Access  
Stat     Hybrid Journal   (Followers: 1)
Stata Journal     Full-text available via subscription   (Followers: 8)
Statistica     Open Access   (Followers: 6)
Statistical Analysis and Data Mining     Hybrid Journal   (Followers: 23)
Statistical Theory and Related Fields     Hybrid Journal  
Statistics and Public Policy     Open Access   (Followers: 4)
Statistics in Transition New Series : An International Journal of the Polish Statistical Association     Open Access  
Statistics Research Letters     Open Access   (Followers: 1)
Statistics, Optimization & Information Computing     Open Access   (Followers: 3)
Stats     Open Access  
Synthesis Lectures on Mathematics and Statistics     Full-text available via subscription   (Followers: 1)
Theory of Probability and its Applications     Hybrid Journal   (Followers: 2)
Theory of Probability and Mathematical Statistics     Full-text available via subscription   (Followers: 2)
Turkish Journal of Forecasting     Open Access   (Followers: 1)
VARIANSI : Journal of Statistics and Its application on Teaching and Research     Open Access  
Zeitschrift für die gesamte Versicherungswissenschaft     Hybrid Journal  


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Nepalese Journal of Statistics
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2565-5213
Published by Nepal Journals Online Homepage  [114 journals]
  • A Note on Confusion between Linear and Affine Functions and the
           Generalized Forms of Gradient

    • Authors: Supriya Malla, Ganesh Malla
      Pages: 1 - 6
      Abstract: Background: Arguably the most frequently used term in science, particularly in mathematics and statistics, is linear. However, confusion arises from the various meanings of linearity instructed in different levels of mathematical courses. The definition of linearity taught in high school is less correct than the one learned in a linear algebra class. The correlation coefficient of two quantitative variables is a numerical measure of the affinity, not only linearity, of two variables. However, every statistics book loosely says it is a measure of linear relationship. This clearly show that there is some confusion between use of the terms the linear function and affine function. Objective: This article aims at clarifying the confusion between use of the terms linear function and affine function. It also provides more generalized forms of the gradient in different branches of mathematics and show their equivalency. Materials and Methods: We have used the pure analytical deductive methods to proof the statements.  Results: We have clearly presented that gradient is the measure of affinity, not just linearity. It becomes a special case of the derivative in calculus, of the least-squares estimate of the regression coefficient in statistics and matrix theory. The gradient can ­­­­be seen in terms of the inverse of the informative matrix in the most general setting of the linear model estimation. Conclusion: The article has been clearly written to show the distinction between the linear and affine functions in a concise and unambiguous manner. We hope that readers will clearly see various generalizations of the gradient and article itself would be a simple exposition, enlightening, and fun to read.
      PubDate: 2021-12-06
      DOI: 10.3126/njs.v5i1.41225
  • Assessment of Factors Associated with Indoor Air Pollution using
           Multinomial Logistic Regression: A Case Study of Barbardiya Municipality

    • Authors: Chitra Raj Bhandari, Srijan Lal Shrestha
      Pages: 7 - 20
      Abstract: Background: Indoor air pollution (IAP) is a major risk factor of acute respiratory infections (ARIs). Most of the households in rural Nepal still depend upon biomass fuel. Associations between socio-economic variables and IAP can be captured using different statistical models. Objectives: The objective of the study was to determine association between IAP condition with socio-economic and demographic factors across the households of Barbardiya municipality, Bardiya, Nepal. Material and Methods: Based upon the primary data of 370 households, association between IAP condition (high, moderate, low) with socio-economic and demographic variables (Ethnicity, education level, income, family size, land size etc.) were established using multinomial logistic regression model.  Results: Descriptive analysis revealed that almost 21% of the households were exposed to high (sever) IAP, 41% to low and rest (38%) were moderate. Fitted model predicted that the odds ratio of socio-economic variables like Ethnicity: Tharu community relative to Bhramin/Chhetri community was 2.5 (95% Confidence Interval (CI): 1.08 -5.78), household head’s education level: illiterate relative to literate was 8.21 (95% CI: 3.30-59.54), family’s monthly income: ≤ NRs 30000 relative to > NRs 30000 was 2.38 (95% CI: 1.10-5.16) considering high with respect to low IAP. Conclusion: Households of Tharu community have significant proportion of high and moderate levels of IAP (or household air pollution) compared to other ethnic groups. Literacy status of household head also have an association with IAP along with several other factors. Various methods can be adopted to reduce IAP which was recommended to concerned authorities.
      PubDate: 2021-12-06
      DOI: 10.3126/njs.v5i1.41226
  • Multinomial Logistic Regression Model for Assessing Factors Associated
           with Junk Food Consumption of Secondary Level Students

    • Authors: Srijana Subedi, Madhav Kumar Bhusal
      Pages: 21 - 38
      Abstract: Background: Globalization, economic progress, urbanization, and industrialization have ushered in considerable changes in lifestyles and diet regimes. Consumption of junk food has surged at a rapid pace nowadays. In Nepal, there is a lack of sufficient research regarding junk food practices and persuading factors for its consumption, among teenage students. It is a global concern and has threatened the health of many people. Objective: This research aims to explore the factors associated with junk food consumption among students of secondary level in Ratnanagar Municipality of Chitwan.  Materials and Methods: A cross-sectional research design consisting of 371 secondary level students, and selection based on primary data collection method by the researchers was used in this study. The data was analyzed using descriptive as well as an inferential statistical method. To find the association of different factors with junk food consumption levels (Low, Moderate, and High) multinomial logistic regression model (MLRM) was used, and the goodness of fit of the model was assessed. Results: The fitted MLRM satisfied the criteria of the diagnostic test including a test of goodness of fit, multi-collinearity test, and minimum criteria of the model utilization with the classification accuracy of 55%. The variables like family monthly income (OR=1.000011, C.I=1.000001 - 1.000020), students’ daily pocket money (OR=1.02, C.I=1.007 - 1.033), gender (OR=0.354, C.I= 0.179 - 0.7), knowledge regarding junk food consumption (OR=2.744, C.I=1.366 - 5.511), attitude towards food choice (OR=2.487, C.I=1.288 – 4.803), friend’s encouragement for junk food consumption (OR=0.178, C.I=0.045 – 0.701), and occupation of father (business) (OR=2.867, C.I=1.084 – 7.581) are seen to be significant to the model High versus Low consumption. Students’ daily pocket money (OR=1.012, C.I=1.002 – 1.023), knowledge regarding junk food consumption (OR=2.427, C.I=1.293 – 4.553), restrictive food parenting practice (OR=2.228, C.I=0.945 – 5.253), friend’s encouragement for junk food consumption (OR=0.252, C.I=0.067 – 0.944), recognition of marketing promotion strategy (OR=0.523, C.I=0.295 – 0.928), educational level of mother (lower secondary level) (OR=5.465, C.I=1.069 – 27.952), occupation of father (business) (OR=2.47, C.I=1.056 – 5.777) are seen to be significant to the model Moderate versus Low consumption. Conclusion:  Study revealed that more than one-fourth of the sampled students were high consumers of junk foods. Many factors are associated with the consumption of junk foods. Thus, addressing the issue of increasing consumption, developing strategies & conducting different research in this field is the must. Concerned authorities should also pay special attention to this subject matter. 
      PubDate: 2021-12-06
      DOI: 10.3126/njs.v5i1.41227
  • Factors Affecting Household Expenditure using OLS Method: A Case Study of
           Ward Number 6 of Sidhalek Rural Municipality, Dhading, Nepal

    • Authors: Krishna Prasad Acharya
      Pages: 39 - 50
      Abstract: Background: The role of annual household expenditure is very important to run a family smoothly. It incorporates the total expenditure of a family who is residing in a house for their livelihood. There are different factors associated with annual household expenditure, and the assessment of them and identification of such factors play a vital role in the concerned area. Objective: To identify the most significant factors associated with annual household expenditure using an appropriate statistical model. Materials and Methods: The study based on cross-sectional study design with 168 households from ward number 6 of Sidhalek rural municipality of Dhading district were considered for the analysis. The multiple linear regression model followed by appropriate bivariate analysis was used to identify the significant factors associated with the outcome variable. Results: Number of literate persons of working age (β = 0.018, 95% CI: 0.004 - 0.032), remittance-receiving status (β = 0.093, 95% CI: 0.026 - 0.160), and gender of household head (β = 0.089, 95% CI: 0.023 - 0.155) was significantly associated with the annual household expenditure. The goodness of fit and diagnostics of the fitted model were also performed. Conclusion: The annual household expenditure is significantly higher among those households having more literate persons of working age, headed by a male and receiving remittance. Considerable improvements need to be made towards the improvements on human capital and remittance-receiving status particularly in the rural area of Nepal.
      PubDate: 2021-12-06
      DOI: 10.3126/njs.v5i1.41228
  • Negative Binomial Distribution to Explain the Domestic Fire Incidence in

    • Authors: Arun Kumar Yadav, Santosh Kumar Shah
      Pages: 51 - 66
      Abstract: Background: Fire disaster is one of the most destructive disasters. According to global dataset of Sendai Framework, domestic fire incidence was 9.9% up to 2019. In Nepal, 62% fire incidence was reported during 2017 and 2018. However, many studies have been conducted on fire incidence, few of them are based on domestic fire incidence. Objective: To find the descriptive statistics of fire occurrences and fire fatalities, and to identify the probability distributions that best fit the data of fire occurrences observed in three ecological regions as well as overall in Nepal. Material and Methods: The data of fire incidences from May 2011 to April 2021 were retrieved from Nepal Disaster Risk Reduction Portal, Government of Nepal. At first, a statistical software "Mathwave EasyFit" of 30 days trial version was used to identify the candidate probability models. Further, the best probability model was determined after testing the goodness of fit of the candidate models by using graphical tools-histogram and theoretical densities, empirical and theoretical CDFs, Q-Q plot and P-P plot; and mathematical tools-maximum likelihood, Akaike Information Criteria and Bayesian Information Criteria by using the package “fitdistrplus” of software R version 4.1.1. Results: On an average, 135 fire incidences per month were occurred in Nepal. However, the Terai faced the highest monthly fire incidences compared to the Hill and the Mountain, it has less fatality per 100 fire incidence followed by the Hill and the Mountain. Descriptive statistics reveals that fire occurrences are moderate during November to February and high in March and April. The fire incidences were reported high during spring and winter and low during summer and autumn season which reveals that fire incidence might be related with the precipitation and temperature. The sample data was run in "Mathwave EasyFit" software which suggested Poisson, geometric and negative binomial distribution as candidate probability models. The goodness of fit of these models were further tested by graphical as well as mathematical tools where negative binomial distribution was found to be best among the candidate models for the data set. Conclusion: Incidence of fire disasters varies by ecological regions as well as by seasons. It is low in the Mountain region and during Monsoon/rainy season. Negative binomial distribution fits the best to monthly data of fire incidence in Nepal.
      PubDate: 2021-12-06
      DOI: 10.3126/njs.v5i1.41229
  • Beta Distribution for Estimating Risk Associated Time Schedule of
           Hydropower Projects in Nepal

    • Authors: Kiran Kumar Shrestha, Rabindra Kayastha
      Pages: 67 - 78
      Abstract: Background: Risk is associated with every kind of project work whether it is related to engineering construction project, software development project, financial transaction process or business process. There isn't any project which is free of risks. It is inherent in all types of projects. Observing risk associated with a project can help in successful completion of projects in expected time and expected cost with good assurance of quality. This article is concerned with quantitative analysis of risks coined with hydropower construction project in Nepal. Objective: The main objective of this paper is (a) to identify different activities involved in hydropower construction projects (b) to estimate risk associated time schedule of the identified project activities. Materials and Methods: Data required for the fulfillment of the objective are obtained by interview and discussion with executives of “Shiva Shree Hydropower Limited” and by using project schedule charts of projects won by the company. In this article quantitative analysis of schedule risk of hydropower project is studied by simulation method. Results: Different activities involved in hydropower construction project are identified. Also, risk associated with time schedule of project are observed quantitatively by simulation using beta-PERT distribution. Conclusion: Estimation of time schedule associated with project activities is more realistic when it is analyzed by using beta-PERT distribution compared to other statistical distributions.
      PubDate: 2021-12-06
      DOI: 10.3126/njs.v5i1.41230
  • Impact of Family Functioning, Family Violence and Other Factors on
           Juvenile Delinquency

    • Authors: Januka Neupane, Pravat Uprety
      Pages: 79 - 94
      Abstract: Background: Juvenile delinquency is the act of participating in unlawful behavior as minors or individuals younger than the age of majority. Nepal shows an increasing trend of violent crimes committed by a juvenile. Objective: To examine the impact of family functioning, family violence, and other family factors on juvenile delinquency. Materials and Methods:  The study is a case-control study based on primary data collection of 354 respondents which include equal number of juvenile delinquents as cases taken from juvenile correction homes and school students as controls who have never been convicted for any act of juvenile delinquency. Data was collected through the convenience sampling method. Structured questionnaire was used to collect data on demographic, socioeconomic, individual and family factors. Bivariate and logistic regression analysis were performed to determine which factor act as a risk or protective factor for juvenile delinquency. Results: From bivariate analysis, family factors such as family functioning, parental monitoring, parental involvement, parental supervision, and parental attachment were found higher in controls than cases. However, family violence was found higher in cases than control group. Further, from fitted logistic regression child age, aggressive behavior, family structure, family financial condition, punitive parenthood, mother education level, and parental attachment were found significant factors impacting on juvenile delinquency. Conclusion: This study revealed that age, aggressive behavior, family structure, and family financial condition are the risk factors for juvenile delinquency. Further, mother education, punitive parenthood, and parental attachment are found protective factors for juvenile delinquency.
      PubDate: 2021-12-06
      DOI: 10.3126/njs.v5i1.41231
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