Pub Date : 2023-05-15DOI: 10.13052/jrss0974-8024.1611
H. Abubakar, Shamsul Rijal Muhammad Sabri
Statistical distributions are of great interest for actuaries in modelling and fitting the distribution of various data sets. It can be used to present a description of risk exposure on the investment, where the level of exposure to the risk can be determined by “key risk indicators” that usually are functions of the statistical model. Financial mathematicians and actuarial scientists often use such key risk indicators to determine the degree to which a particular company is subject to certain aspects of risk, which arise from changes in underlying variables such as prices of equity, interest rates fluctuations, or exchange rates. Weibull distribution is one of the most popular statistical distribution models employed by the actuarial and financial risk management problems in fitting and or in modelling the behaviours of financial data or lifetime event data to forecast stock pricing movement or uncertainly prediction. In this study, a Bayesian approach to the Weibull distribution model on the assumption of gamma prior to Weibull distribution parameters has been proposed. A computational study based on the actuarial measures is conducted, proving the proposed distribution of the claim amount. Along this line, in assessing the performance of the proposed method, the results of the simulations study have been conducted to explore the efficiency of the proposed estimators is compared to a maximum likelihood (MLE) and simulated annealing algorithm (SA). Finally, an actuarial real data set is analyzed, proving that the proposed model can be used effectively to model insurance claim data.
{"title":"A Bayesian Approach to Weibull Distribution with Application to Insurance Claims Data","authors":"H. Abubakar, Shamsul Rijal Muhammad Sabri","doi":"10.13052/jrss0974-8024.1611","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1611","url":null,"abstract":"Statistical distributions are of great interest for actuaries in modelling and fitting the distribution of various data sets. It can be used to present a description of risk exposure on the investment, where the level of exposure to the risk can be determined by “key risk indicators” that usually are functions of the statistical model. Financial mathematicians and actuarial scientists often use such key risk indicators to determine the degree to which a particular company is subject to certain aspects of risk, which arise from changes in underlying variables such as prices of equity, interest rates fluctuations, or exchange rates. Weibull distribution is one of the most popular statistical distribution models employed by the actuarial and financial risk management problems in fitting and or in modelling the behaviours of financial data or lifetime event data to forecast stock pricing movement or uncertainly prediction. In this study, a Bayesian approach to the Weibull distribution model on the assumption of gamma prior to Weibull distribution parameters has been proposed. A computational study based on the actuarial measures is conducted, proving the proposed distribution of the claim amount. Along this line, in assessing the performance of the proposed method, the results of the simulations study have been conducted to explore the efficiency of the proposed estimators is compared to a maximum likelihood (MLE) and simulated annealing algorithm (SA). Finally, an actuarial real data set is analyzed, proving that the proposed model can be used effectively to model insurance claim data.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45492479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-06DOI: 10.13052/jrss0974-8024.15212
Sapna Saini, J. Kumar, M. S. Kadyan
The continuous casting system is the most important to solidify the liquid steel in the steel industry. Steel is the backbone of civilization and modernization. So, there is a need to optimize the performance of continuous casting system of steel industry. Continuous casting system has six subsystems: “Pouring turret ladle”, “Tundish”, “Mold”, “Water spray chamber”, “Support roller” and “Torch cutter”. Series configuration is used to arrange these subsystems. The subsystem “Pouring turret ladle” is having three similar units. These units are operating in parallel. The subsystems “Tundish”, “Mold”, “Water spray chamber” and “Support roller” have a single unit. The subsystem “Torch cutter” contains two identical units: one is operative and other keep in cold standby. For all subsystems, the distribution of repair rates and failure rates of continuous casting system are taken as arbitrary distributions. Analysis of continuous casting system has been done by using supplementary variable technique. The numerical results of reliability measure of continuous casting system in terms of availability and profit have been computed by assuming exponential, Rayleigh and Weibull distributions.
{"title":"Performance Analysis of Continuous Casting System of Steel Industry","authors":"Sapna Saini, J. Kumar, M. S. Kadyan","doi":"10.13052/jrss0974-8024.15212","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.15212","url":null,"abstract":"The continuous casting system is the most important to solidify the liquid steel in the steel industry. Steel is the backbone of civilization and modernization. So, there is a need to optimize the performance of continuous casting system of steel industry. Continuous casting system has six subsystems: “Pouring turret ladle”, “Tundish”, “Mold”, “Water spray chamber”, “Support roller” and “Torch cutter”. Series configuration is used to arrange these subsystems. The subsystem “Pouring turret ladle” is having three similar units. These units are operating in parallel. The subsystems “Tundish”, “Mold”, “Water spray chamber” and “Support roller” have a single unit. The subsystem “Torch cutter” contains two identical units: one is operative and other keep in cold standby. For all subsystems, the distribution of repair rates and failure rates of continuous casting system are taken as arbitrary distributions. Analysis of continuous casting system has been done by using supplementary variable technique. The numerical results of reliability measure of continuous casting system in terms of availability and profit have been computed by assuming exponential, Rayleigh and Weibull distributions.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42612123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-06DOI: 10.13052/jrss0974-8024.15215
Siqiao Li, T. Dohi, H. Okamura
In this paper, we propose a new non-homogeneous Poisson process (NHPP) based software reliability model (SRM), where the software debug rate is given by a local polynomial function. The main feature of this semi-parametric SRM is to control the goodness-of-fit by changing the polynomial degree. Numerical examples with 16 actual software development project data are devoted to comparing our SRM with the well-known existing NHPP-based SRMs in terms of goodness-of-fit and predictive performances.
{"title":"A Semi-parametric NHPP-based Software Reliability Modeling with Local Polynomial Debug Rate","authors":"Siqiao Li, T. Dohi, H. Okamura","doi":"10.13052/jrss0974-8024.15215","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.15215","url":null,"abstract":"In this paper, we propose a new non-homogeneous Poisson process (NHPP) based software reliability model (SRM), where the software debug rate is given by a local polynomial function. The main feature of this semi-parametric SRM is to control the goodness-of-fit by changing the polynomial degree. Numerical examples with 16 actual software development project data are devoted to comparing our SRM with the well-known existing NHPP-based SRMs in terms of goodness-of-fit and predictive performances.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43453601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-06DOI: 10.13052/jrss0974-8024.15214
M. Devi, T. Sumathi, Uma Maheshwari, A. Satyanarayana
In this paper, reliability of simply supported I-beam is studied under point load at the mid-point of span. Reliability index has been obtained by using Hasofer-Lind method. In the analysis, yield strength of material, depth of the section and load are considered as basic random variables and those are assumed to follow normal distribution. Non-linear limit state surface function has been considered. Derived design point in each case and found the reliability.
{"title":"Reliability Index of Simply Supported Beam Based on HL Method","authors":"M. Devi, T. Sumathi, Uma Maheshwari, A. Satyanarayana","doi":"10.13052/jrss0974-8024.15214","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.15214","url":null,"abstract":"In this paper, reliability of simply supported I-beam is studied under point load at the mid-point of span. Reliability index has been obtained by using Hasofer-Lind method. In the analysis, yield strength of material, depth of the section and load are considered as basic random variables and those are assumed to follow normal distribution. Non-linear limit state surface function has been considered. Derived design point in each case and found the reliability.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43908641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-06DOI: 10.13052/jrss0974-8024.15213
M. Tripathy, P. Swain, P. K. Sarangi, S. Pattnaik
The objective of this study is to determine the significant predictors of endometrial cancer using accelerated failure time models (AFTM). We have demonstrated the applications of AFTM viz. Exponential, Weibull, Log-normal, Log-logistic, Gompertz, Gamma and Generalized Gamma AFTM, as an alternative of Cox proportional hazard model. Data for the analysis was collected from Acharya Harihar Post Graduate Institute of Cancer (AHPGIC), Cuttack, Odisha during the period 2016–20. Based on the lowest Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) value, the Weibull AFTM has been chosen as the best fitted AFT model. The predictors such as age, comorbidity, tumor size, isolated para-aortic and adnexa have been found as significant predictors (p-value < 0.05) to explain the survival of endometrial cancer patients. Hence, by optimizing different treatments, based on such prognostic factors plays an important role in managing endometrial cancer at an early stage.
{"title":"Accelerated Failure Time Models with Applications to Endometrial Cancer Survival Data","authors":"M. Tripathy, P. Swain, P. K. Sarangi, S. Pattnaik","doi":"10.13052/jrss0974-8024.15213","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.15213","url":null,"abstract":"The objective of this study is to determine the significant predictors of endometrial cancer using accelerated failure time models (AFTM). We have demonstrated the applications of AFTM viz. Exponential, Weibull, Log-normal, Log-logistic, Gompertz, Gamma and Generalized Gamma AFTM, as an alternative of Cox proportional hazard model. Data for the analysis was collected from Acharya Harihar Post Graduate Institute of Cancer (AHPGIC), Cuttack, Odisha during the period 2016–20. Based on the lowest Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) value, the Weibull AFTM has been chosen as the best fitted AFT model. The predictors such as age, comorbidity, tumor size, isolated para-aortic and adnexa have been found as significant predictors (p-value < 0.05) to explain the survival of endometrial cancer patients. Hence, by optimizing different treatments, based on such prognostic factors plays an important role in managing endometrial cancer at an early stage.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47611985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.13052/jrss0974-8024.15211
Garima Chopra, M. Ram
The concerned study pertains to the development of a new stochastic model for the reliability analysis of linear consecutive-k-out-of-n: G system, where k>n2. In the developed model, system may collapse as a result of common cause failure or hardware failure in its units. The system has exponentially distributed failure rates, and in case of breakdown, it is repaired with the copula method. The developed model has been examined through supplementary variable technique (SVT) along with Laplace transform. The current paper has specifically studied consecutive-(n-1)-out-of-n: G system. The performance of such system having ten components is explored and its various reliability measures have been obtained and discussed with the help of graphs. The originality of this work lies in incorporating common cause failure in conjunction with copula repair in the reliability modeling of consecutive systems through the SVT. The study confirms that an increase in failure rates and the number of components of the concerned system decreases mean time to failure (MTTF). The profit of linear consecutive-9-out-of-10: G system is examined with the help of a numerical example.
{"title":"Linear Consecutive-k-out-of-n: G System Reliability Analysis","authors":"Garima Chopra, M. Ram","doi":"10.13052/jrss0974-8024.15211","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.15211","url":null,"abstract":"The concerned study pertains to the development of a new stochastic model for the reliability analysis of linear consecutive-k-out-of-n: G system, where k>n2. In the developed model, system may collapse as a result of common cause failure or hardware failure in its units. The system has exponentially distributed failure rates, and in case of breakdown, it is repaired with the copula method. The developed model has been examined through supplementary variable technique (SVT) along with Laplace transform. The current paper has specifically studied consecutive-(n-1)-out-of-n: G system. The performance of such system having ten components is explored and its various reliability measures have been obtained and discussed with the help of graphs. The originality of this work lies in incorporating common cause failure in conjunction with copula repair in the reliability modeling of consecutive systems through the SVT. The study confirms that an increase in failure rates and the number of components of the concerned system decreases mean time to failure (MTTF). The profit of linear consecutive-9-out-of-10: G system is examined with the help of a numerical example.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":"1 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42046894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-23DOI: 10.13052/jrss0974-8024.15210
Mohamed S. Abdallah
The ranked set sampling (RSS) is an effective scheme popularly used to produce more precisely estimators. Despite its popularity, RSS suffers from some drawbacks which includes high sensitivity to outliers and it cannot sometimes be applicable when the population is relatively small. To overcome these limitations, varied L ranked set sampling (VLRSS) is recently introduced. It is shown that VLRSS scheme enjoys with many interesting properties over RSS and also encompasses several existing RSS schemes. In addition, it is also helpful for providing precise estimates of several population parameters. To fill this gap, this article extends the work and address the estimation of based ℛ on VLRSS when the strength and stress both follow exponential distribution. Maximum likelihood approach as well as Bayesian method are considered for estimating ℛ. The Bayes estimators are obtained by using gamma distribution under general entropy loss function and LINEX loss function. The performance of the estimators based on VLRSS are investigated by a simulation study as well as a real dataset relevant to industrial field. The results reveal that the proposed estimators are more efficient relative to their analogues estimators under L ranked set sampling given that the quality of ranking is fairly good.
{"title":"Bayesian and MLE of R=P(Y>X) for Exponential Distribution Based on Varied L Ranked Set Sampling","authors":"Mohamed S. Abdallah","doi":"10.13052/jrss0974-8024.15210","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.15210","url":null,"abstract":"The ranked set sampling (RSS) is an effective scheme popularly used to produce more precisely estimators. Despite its popularity, RSS suffers from some drawbacks which includes high sensitivity to outliers and it cannot sometimes be applicable when the population is relatively small. To overcome these limitations, varied L ranked set sampling (VLRSS) is recently introduced. It is shown that VLRSS scheme enjoys with many interesting properties over RSS and also encompasses several existing RSS schemes. In addition, it is also helpful for providing precise estimates of several population parameters. To fill this gap, this article extends the work and address the estimation of based ℛ on VLRSS when the strength and stress both follow exponential distribution. Maximum likelihood approach as well as Bayesian method are considered for estimating ℛ. The Bayes estimators are obtained by using gamma distribution under general entropy loss function and LINEX loss function. The performance of the estimators based on VLRSS are investigated by a simulation study as well as a real dataset relevant to industrial field. The results reveal that the proposed estimators are more efficient relative to their analogues estimators under L ranked set sampling given that the quality of ranking is fairly good.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46627527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-30DOI: 10.13052/jrss0974-8024.1528
Sudeep Kumar, Ritu Gupta
In industrial systems, the K-out-of-N: G system is a prominent type of redundancy. The load sharing protects such system from malfunctioning/destroying and avoids overload problem that affects the system reliability in a significant manner. In this paper we develop a Markovian model of load-sharing K-out-of-N: G system having non-identical repairable components wherein the server may on working vacation. During his vacation period, the server repairs the failed components with different service rates rather than completely terminating service rate. The failed component gets immediately repaired by the server if not on vacation, and unequal load is distributed among remaining surviving components. The lifetime of each component is load dependent followed by non-identical exponential distribution with different failure rates. The system is failed down due to common cause with failure density which is also exponentially distributed. We suggest closed structure analytic expressions for reliability, cost estimation and other performance measures of the load-sharing K-out-of-N: G repairable system by incorporating the concept of working vacation. For the solution aspiration, Runge-Kutta method is utilized to solve the system of differential equations. Furthermore, we perform the numerical analysis for two illustrations 1-out-of-3: G system and 3-out-of-4: G system. The numerical simulation is carried out for the validation of analytical results which are exhibited and compared by giving numerical outcomes and neuro-fuzzy outcomes based on fuzzy interference system with the help of MATLAB.
{"title":"Working Vacation Policy for Load Sharing K-out-of-N: G System","authors":"Sudeep Kumar, Ritu Gupta","doi":"10.13052/jrss0974-8024.1528","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1528","url":null,"abstract":"In industrial systems, the K-out-of-N: G system is a prominent type of redundancy. The load sharing protects such system from malfunctioning/destroying and avoids overload problem that affects the system reliability in a significant manner. In this paper we develop a Markovian model of load-sharing K-out-of-N: G system having non-identical repairable components wherein the server may on working vacation. During his vacation period, the server repairs the failed components with different service rates rather than completely terminating service rate. The failed component gets immediately repaired by the server if not on vacation, and unequal load is distributed among remaining surviving components. The lifetime of each component is load dependent followed by non-identical exponential distribution with different failure rates. The system is failed down due to common cause with failure density which is also exponentially distributed. We suggest closed structure analytic expressions for reliability, cost estimation and other performance measures of the load-sharing K-out-of-N: G repairable system by incorporating the concept of working vacation. For the solution aspiration, Runge-Kutta method is utilized to solve the system of differential equations. Furthermore, we perform the numerical analysis for two illustrations 1-out-of-3: G system and 3-out-of-4: G system. The numerical simulation is carried out for the validation of analytical results which are exhibited and compared by giving numerical outcomes and neuro-fuzzy outcomes based on fuzzy interference system with the help of MATLAB.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":"1 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41972958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-30DOI: 10.13052/jrss0974-8024.1529
J. T. Eghwerido, Suraju Olaniyi Ogundele, L. Nzei, F. Agu
This article introduced the determination of reliability analysis of the alpha power Gompertz model using the Bayesian techniques. The method developed has been evaluated using women breast cancer in the Stan implementation in R. A survival data used illustrates the proposed Bayesian approach.
{"title":"The Bayesian Reliability Analysis of the Alpha Power Gompertz Model","authors":"J. T. Eghwerido, Suraju Olaniyi Ogundele, L. Nzei, F. Agu","doi":"10.13052/jrss0974-8024.1529","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1529","url":null,"abstract":"This article introduced the determination of reliability analysis of the alpha power Gompertz model using the Bayesian techniques. The method developed has been evaluated using women breast cancer in the Stan implementation in R. A survival data used illustrates the proposed Bayesian approach.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45973895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-03DOI: 10.13052/jrss0974-8024.1526
Prayas Sharma, N. K. Adichwal, A. K. Singh
Corona viruses, commonly called COVID-19, are a large family of viruses that can cause diseases ranging from the common cold to Severe Acute Respiratory Syndrome (SARS). Worldwide Covid-19 is affecting 210 countries and territories around the world and two international conveyances. As of 2 June 2020, there are 6,408,869 confirmed 2,935,368 recovered and 378,317 deaths cases has been reported in world of Coronavirus diseases, India is not untouched from this situation. Currently, it has reported infected 190,535 and 5,394 death cases due to COVID-19 in India. (https://covid19.who.int/region/searo/country/in). The COVID-19 pandemic was first confirmed in the Indian state of Uttar Pradesh on 4 March 2020, with the first positive case in Ghaziabad. As of 1 June 2020, the state has 8361 confirmed cases, resulting in 222 deaths and 5030 recoveries. The situation is getting worst day by day as COVID-19 outbreaks and patients are increasing by every minute and become the most important issue for the whole world and So accessing knowledge and awareness among the people is very important. The present study using the exploratory data analysis we tried to demonstrate the knowledge and awareness of individuals about the COVID-19 pandemic in Uttar Pradesh, the most populous state of India. The findings of the present study can be utilized by the researchers and policy makers to handle this worst situation.
{"title":"Knowledge and Awareness of COVID-19 in Uttar Pradesh: An Exploratory Data Analysis","authors":"Prayas Sharma, N. K. Adichwal, A. K. Singh","doi":"10.13052/jrss0974-8024.1526","DOIUrl":"https://doi.org/10.13052/jrss0974-8024.1526","url":null,"abstract":"Corona viruses, commonly called COVID-19, are a large family of viruses that can cause diseases ranging from the common cold to Severe Acute Respiratory Syndrome (SARS). Worldwide Covid-19 is affecting 210 countries and territories around the world and two international conveyances. As of 2 June 2020, there are 6,408,869 confirmed 2,935,368 recovered and 378,317 deaths cases has been reported in world of Coronavirus diseases, India is not untouched from this situation. Currently, it has reported infected 190,535 and 5,394 death cases due to COVID-19 in India. (https://covid19.who.int/region/searo/country/in). The COVID-19 pandemic was first confirmed in the Indian state of Uttar Pradesh on 4 March 2020, with the first positive case in Ghaziabad. As of 1 June 2020, the state has 8361 confirmed cases, resulting in 222 deaths and 5030 recoveries. The situation is getting worst day by day as COVID-19 outbreaks and patients are increasing by every minute and become the most important issue for the whole world and So accessing knowledge and awareness among the people is very important. The present study using the exploratory data analysis we tried to demonstrate the knowledge and awareness of individuals about the COVID-19 pandemic in Uttar Pradesh, the most populous state of India. The findings of the present study can be utilized by the researchers and policy makers to handle this worst situation.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45343255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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