Pub Date : 2018-06-01DOI: 10.11648/J.SJAMS.20180603.11
D. Dana
Fertility is one of the elements in population dynamics that has a significant contribution towards changing population size and structure overtime. The aim of objective of this study is to identify Demographic, Socio-economic, and Cultural factors that affect Fertility level among women of childbearing age in Ethiopia. The data for this study were taken from Ethiopia Demographic and Health Survey conducted in 2011 (EDHS2011). For modelling purpose binary logistic regression was used and data were analyzed using SPSS Version16. The total number of women in childbearing age is based on10,897 women who have at least one child and whose age ranges from15 to 49 years. Among these, 8130 (74.6%) reside in rural areas where as 2767 (25.4%) reside in urban hubs. Among those individuals 64.2% were currently not working and the remaining 35.8% of the respondent were categorized under currently working group. In relation to age at first Cohabitation, about 37.7% of individuals were fail under 15-17 interval of age category and 34.5% of respondent were greater than or equal to 18 years old. The majority of individuals were married 8621 (79.1%), followed by divorced and living with partner (716 (6.6%) and living with partner 588 (5.4%) respectively). In the analyses, all the variables Region, women educational level, wealth index, husband’s/partner’s educational level, marital status, age at first cohabitation and age in 5-years group were found to have significant effect on total number of child ever born at significance level of 5%. From the fitted logistic regression model, the estimates odds ratio displayed in table 5, for the variable region reference category is Addis Ababa. The value of the odds ratio for region that the odds of having TCEB greater than or equals to five children for Tigray region is have 38.4% more than those individuals in Addis Ababa (OR=1.384, C.I=1.055-1.810) and its effect is statistically significant.
生育率是人口动态中的一个因素，随着时间的推移，对改变人口规模和结构有重大贡献。本研究的目的是确定影响埃塞俄比亚育龄妇女生育水平的人口、社会经济和文化因素。本研究的数据取自2011年进行的埃塞俄比亚人口与健康调查(EDHS2011)。为了建模目的，使用二元逻辑回归，并使用SPSS Version16对数据进行分析。育龄妇女总数为10897名至少有一个孩子的妇女，年龄在15岁至49岁之间。其中，8130人(74.6%)居住在农村地区，2767人(25.4%)居住在城市中心。在这些人中，64.2%目前没有工作，其余35.8%的受访者属于目前的工作小组。就首次同居年龄而言，约37.7%的受访者年龄介乎15至17岁，34.5%的受访者年龄介乎18岁或以上。以已婚人士8621人(79.1%)居多，其次为离婚及与伴侣同居人士(716人(6.6%))及与伴侣同居人士(588人(5.4%))。在分析中，所有变量地区、女性受教育程度、财富指数、丈夫/伴侣受教育程度、婚姻状况、首次同居年龄和5岁组年龄对总出生人数都有显著影响，显著性水平为5%。从拟合的logistic回归模型中，表5所示的估计比值比，变量区域参考类别为亚的斯亚贝巴。亚的斯亚贝巴地区TCEB大于等于5个孩子的地区比值比值为38.4% (or =1.384, ci =1.055 ~ 1.810)，差异有统计学意义。
{"title":"Binary Logistic Regression Analysis of Identifying Demographic, Socioeconomic, and Cultural Factors that Affect Fertility Among Women of Child bearing Age in Ethiopia","authors":"D. Dana","doi":"10.11648/J.SJAMS.20180603.11","DOIUrl":"https://doi.org/10.11648/J.SJAMS.20180603.11","url":null,"abstract":"Fertility is one of the elements in population dynamics that has a significant contribution towards changing population size and structure overtime. The aim of objective of this study is to identify Demographic, Socio-economic, and Cultural factors that affect Fertility level among women of childbearing age in Ethiopia. The data for this study were taken from Ethiopia Demographic and Health Survey conducted in 2011 (EDHS2011). For modelling purpose binary logistic regression was used and data were analyzed using SPSS Version16. The total number of women in childbearing age is based on10,897 women who have at least one child and whose age ranges from15 to 49 years. Among these, 8130 (74.6%) reside in rural areas where as 2767 (25.4%) reside in urban hubs. Among those individuals 64.2% were currently not working and the remaining 35.8% of the respondent were categorized under currently working group. In relation to age at first Cohabitation, about 37.7% of individuals were fail under 15-17 interval of age category and 34.5% of respondent were greater than or equal to 18 years old. The majority of individuals were married 8621 (79.1%), followed by divorced and living with partner (716 (6.6%) and living with partner 588 (5.4%) respectively). In the analyses, all the variables Region, women educational level, wealth index, husband’s/partner’s educational level, marital status, age at first cohabitation and age in 5-years group were found to have significant effect on total number of child ever born at significance level of 5%. From the fitted logistic regression model, the estimates odds ratio displayed in table 5, for the variable region reference category is Addis Ababa. The value of the odds ratio for region that the odds of having TCEB greater than or equals to five children for Tigray region is have 38.4% more than those individuals in Addis Ababa (OR=1.384, C.I=1.055-1.810) and its effect is statistically significant.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114983437","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 : 2018-05-25DOI: 10.11648/J.SJAMS.20180602.12
L. Brew, J. Acquah, F. Nyarko, Amidu Mohammed
This paper studies the migration trends of rural and urban populations in Ghana. The matrix method approximately determines the new population percentage values of rural and urban areas in Ghana from 2016 to 2020. The 2015 rural and urban population values were used as initial values for the projection of the other subsequent population values. The graph matrix and clustered column chart examined the trends relationship between rural and urban populations. The emerging trends of population migration at the rural and urban areas were discussed. The method revealed the upward and downward trends of populations in urban and rural areas. The accuracy of the method is proven by comparing the estimated results from the matrix method with those obtained from the website of index mundi in the literature. On the bases of these findings, the paper recommends the steps to be taken by the government and other policy makers in Ghana to avert excessive migration flow in the urban and rural areas respectively.
{"title":"Matrix Dynamics of Migration Trends of Rural-Urban Population in Ghana","authors":"L. Brew, J. Acquah, F. Nyarko, Amidu Mohammed","doi":"10.11648/J.SJAMS.20180602.12","DOIUrl":"https://doi.org/10.11648/J.SJAMS.20180602.12","url":null,"abstract":"This paper studies the migration trends of rural and urban populations in Ghana. The matrix method approximately determines the new population percentage values of rural and urban areas in Ghana from 2016 to 2020. The 2015 rural and urban population values were used as initial values for the projection of the other subsequent population values. The graph matrix and clustered column chart examined the trends relationship between rural and urban populations. The emerging trends of population migration at the rural and urban areas were discussed. The method revealed the upward and downward trends of populations in urban and rural areas. The accuracy of the method is proven by comparing the estimated results from the matrix method with those obtained from the website of index mundi in the literature. On the bases of these findings, the paper recommends the steps to be taken by the government and other policy makers in Ghana to avert excessive migration flow in the urban and rural areas respectively.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130036129","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 : 2018-05-22DOI: 10.11648/j.sjams.20180602.11
S. Mukherjee, T. K. Garai
Background: The present article tries to analyze a correlated spatiotemporal data using an advance regression modeling techniques. Spatiotemporal data contains the information of both space and time simultaneously. Naturally, it is very much complicated and not easy to model. This article focuses on some modeling techniques to analyze a correlated spatiotemporal agricultural dataset. This dataset contains information of soil parameters for five years across the twenty six different locations with their geographical status in term of longitude and latitude. Soil pH and fertility index are the two major limiting factors in agriculture. These two parameters are governed by many other factors viz. fertilizer use, cropping intensity, soil type, geographical location, soil health management etc. Objective: The present study has been set up to explore whether there is any spatial gradient in the average pH levels across the geographical locations while fertility index and cropping intensity are acting as possible confounder. Methods: Soil pH is the response variable which varies with respect to time and space generally has a correlated structure. Besides this, some random effects component with fixed effects having a nonlinear association with the response is observed here. Generalized additive mixed model (GAMM) regression and Bivariate Smoothing techniques have been exercised to arrive at a meaningful conclusion. Conclusions: It is found that the pH value varies with change in latitude. Besides this, year, fertility index of available potassium and phosphate are also significant cofactors of this study. Final model has been selected through minimum AIC value (204.9) and model checking plots.
{"title":"Correlated Spatiotemporal Data Modeling Using Generalized Additive Mixed Model and Bivariate Smoothing Techniques","authors":"S. Mukherjee, T. K. Garai","doi":"10.11648/j.sjams.20180602.11","DOIUrl":"https://doi.org/10.11648/j.sjams.20180602.11","url":null,"abstract":"Background: The present article tries to analyze a correlated spatiotemporal data using an advance regression modeling techniques. Spatiotemporal data contains the information of both space and time simultaneously. Naturally, it is very much complicated and not easy to model. This article focuses on some modeling techniques to analyze a correlated spatiotemporal agricultural dataset. This dataset contains information of soil parameters for five years across the twenty six different locations with their geographical status in term of longitude and latitude. Soil pH and fertility index are the two major limiting factors in agriculture. These two parameters are governed by many other factors viz. fertilizer use, cropping intensity, soil type, geographical location, soil health management etc. Objective: The present study has been set up to explore whether there is any spatial gradient in the average pH levels across the geographical locations while fertility index and cropping intensity are acting as possible confounder. Methods: Soil pH is the response variable which varies with respect to time and space generally has a correlated structure. Besides this, some random effects component with fixed effects having a nonlinear association with the response is observed here. Generalized additive mixed model (GAMM) regression and Bivariate Smoothing techniques have been exercised to arrive at a meaningful conclusion. Conclusions: It is found that the pH value varies with change in latitude. Besides this, year, fertility index of available potassium and phosphate are also significant cofactors of this study. Final model has been selected through minimum AIC value (204.9) and model checking plots.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131024865","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 : 2018-02-24DOI: 10.11648/J.SJAMS.20180601.15
Nedal Hassan Elbadowi Eljaneid
The main objective of the Variational inequality problem is to study some functional analytic tools, projection method and fixed point theorems and then exploiting these to study the existence of solutions and convergence analysis of iterative algorithms developed for some classes of Variational inequality problem. The main objective of this paper is to study the existence of solutions of some classes of Variational inequalities using fixed point theorems for multivalued and using Banach contraction theorem we prove the existence of a unique solution of multi value Variational inequality problem.
{"title":"A Classes of Variational Inequality Problems Involving Multivalued Mappings","authors":"Nedal Hassan Elbadowi Eljaneid","doi":"10.11648/J.SJAMS.20180601.15","DOIUrl":"https://doi.org/10.11648/J.SJAMS.20180601.15","url":null,"abstract":"The main objective of the Variational inequality problem is to study some functional analytic tools, projection method and fixed point theorems and then exploiting these to study the existence of solutions and convergence analysis of iterative algorithms developed for some classes of Variational inequality problem. The main objective of this paper is to study the existence of solutions of some classes of Variational inequalities using fixed point theorems for multivalued and using Banach contraction theorem we prove the existence of a unique solution of multi value Variational inequality problem.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128851182","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 : 2018-02-11DOI: 10.11648/j.sjams.20180601.14
A. Anekeya, O. Onyango, Nyongesa L. Kennedy
This paper describes theoretical estimation of domains mean using double sampling with a non-linear cost function in the presence of non-response. The estimation of domain mean is proposed using auxiliary information in which the study and auxiliary variable suffers from non-response in the second phase sampling. The expression of the biases and mean square errors of the proposed estimators are obtained. The optimal stratum sample sizes for given set of non-linear cost function are developed.
{"title":"Domain Mean Estimation Using Double Sampling with Non-Linear Cost Function in the Presence of Non Response","authors":"A. Anekeya, O. Onyango, Nyongesa L. Kennedy","doi":"10.11648/j.sjams.20180601.14","DOIUrl":"https://doi.org/10.11648/j.sjams.20180601.14","url":null,"abstract":"This paper describes theoretical estimation of domains mean using double sampling with a non-linear cost function in the presence of non-response. The estimation of domain mean is proposed using auxiliary information in which the study and auxiliary variable suffers from non-response in the second phase sampling. The expression of the biases and mean square errors of the proposed estimators are obtained. The optimal stratum sample sizes for given set of non-linear cost function are developed.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115413211","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 : 2018-02-01DOI: 10.11648/j.sjams.20180601.13
O. Antwi, F. Oduro
We present a succinct new approach to derive the Black-Scholes partial differential equation and subsequently the Black-Scholes formula. We proceed to use the formula to price options using stocks listed on Ghana stock exchange as underlying assets. From one year historical stock prices we obtain volatilities of the listed stocks which are subsequently used to compute prices of three month European call option. The results indicate that it is possible to use the Black Scholes formula to price options on the stocks listed on exchange. However, it was realised that most call option prices tend to zero either due to very low volatilities or very low stock prices. On the other hand put options were found to give positive prices even for stocks with very low volatilities or low stock prices.
{"title":"Pricing Options on Ghanaian Stocks Using Black-Scholes Model","authors":"O. Antwi, F. Oduro","doi":"10.11648/j.sjams.20180601.13","DOIUrl":"https://doi.org/10.11648/j.sjams.20180601.13","url":null,"abstract":"We present a succinct new approach to derive the Black-Scholes partial differential equation and subsequently the Black-Scholes formula. We proceed to use the formula to price options using stocks listed on Ghana stock exchange as underlying assets. From one year historical stock prices we obtain volatilities of the listed stocks which are subsequently used to compute prices of three month European call option. The results indicate that it is possible to use the Black Scholes formula to price options on the stocks listed on exchange. However, it was realised that most call option prices tend to zero either due to very low volatilities or very low stock prices. On the other hand put options were found to give positive prices even for stocks with very low volatilities or low stock prices.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124823738","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 : 2018-01-31DOI: 10.11648/J.SJAMS.20180601.12
Thomas Mageto, E. Njuguna, Dolleen Osundwa
This study sought to model risk factors of diabetes (A case study of Focus Medical Center in Kiambu, Kenya) for the year 2016. We considered sample of size 181 patients and carried descriptive statistics, bivariate analysis, Chi-Square test and Hosmer and Lemeshow test. The independence test between response variable (diabetes) and predictor variables (age, obesity, alcohol, smoking and hypertension) was carried. The variables age, obesity, alcohol and hypertension were found to be statistically significant at α =0.05 level of significant. A multiple logistic regression model was fitted and the fitted regression model indicated that the predictor variables age, obesity and alcohol were statistically significant. The results of the odds ratios show that age, obesity and alcohol consumption are positively associated with diabetes. The fitted reduced multiple logistic regression model was subjected to an overall goodness-of-fit test and results indicate that there is no significant difference between the observed and predicted probability. Based on the results of this study, we recommend that special attention should be given to individuals advanced in age, consume alcohol or who are obese for screening as there is a high possibility of testing positive for diabetes for health care givers to monitor and manage the condition. Further, healthy lifestyles should be promoted among the general population and in particular, the diabetic patients to increase the chance of properly managing the condition. A further study ought to be conducted to assess treatment interventions of diabetes to ascertain the effectiveness and recommend the best medication for patients suffering from diabetes.
本研究试图模拟2016年糖尿病的危险因素(以肯尼亚Kiambu的Focus医疗中心为例)。我们考虑样本量为181例患者，并进行描述性统计、双变量分析、卡方检验和Hosmer and Lemeshow检验。对反应变量(糖尿病)与预测变量(年龄、肥胖、饮酒、吸烟、高血压)进行独立检验。年龄、肥胖、酒精、高血压等变量在α =0.05显著水平上差异有统计学意义。对多元logistic回归模型进行拟合，拟合后的回归模型显示，年龄、肥胖、酒精等预测变量具有统计学意义。比值比结果显示，年龄、肥胖和饮酒与糖尿病呈正相关。拟合的简化多元逻辑回归模型进行了整体拟合优度检验，结果表明，观测概率与预测概率之间没有显著差异。基于这项研究的结果，我们建议特别关注年龄较大、饮酒或肥胖的个体进行筛查，因为卫生保健提供者监测和管理糖尿病的可能性很高。此外，应在一般人群中，特别是糖尿病患者中推广健康的生活方式，以增加适当控制病情的机会。应该进行进一步的研究来评估糖尿病的治疗干预措施，以确定其有效性，并为糖尿病患者推荐最佳药物。
{"title":"Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016)","authors":"Thomas Mageto, E. Njuguna, Dolleen Osundwa","doi":"10.11648/J.SJAMS.20180601.12","DOIUrl":"https://doi.org/10.11648/J.SJAMS.20180601.12","url":null,"abstract":"This study sought to model risk factors of diabetes (A case study of Focus Medical Center in Kiambu, Kenya) for the year 2016. We considered sample of size 181 patients and carried descriptive statistics, bivariate analysis, Chi-Square test and Hosmer and Lemeshow test. The independence test between response variable (diabetes) and predictor variables (age, obesity, alcohol, smoking and hypertension) was carried. The variables age, obesity, alcohol and hypertension were found to be statistically significant at α =0.05 level of significant. A multiple logistic regression model was fitted and the fitted regression model indicated that the predictor variables age, obesity and alcohol were statistically significant. The results of the odds ratios show that age, obesity and alcohol consumption are positively associated with diabetes. The fitted reduced multiple logistic regression model was subjected to an overall goodness-of-fit test and results indicate that there is no significant difference between the observed and predicted probability. Based on the results of this study, we recommend that special attention should be given to individuals advanced in age, consume alcohol or who are obese for screening as there is a high possibility of testing positive for diabetes for health care givers to monitor and manage the condition. Further, healthy lifestyles should be promoted among the general population and in particular, the diabetic patients to increase the chance of properly managing the condition. A further study ought to be conducted to assess treatment interventions of diabetes to ascertain the effectiveness and recommend the best medication for patients suffering from diabetes.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131140007","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 : 2018-01-12DOI: 10.11648/j.sjams.20180601.11
Md. Shakhawat Hossain, M. Rokonuzzaman
In this study, the impact of stock market, trade and credit by bank on economic growth for nine Latin American countries are examined. Fixed effect panel model with dummy variable approach is used in this research work. Significant Hausman test statistic conferred for fixed effect panel model to analyze this dataset. The inflation rate, import and credit by banking sector have negative impact on GDP growth whereas the rest of the variables, exports, stock market, board money, credit by private sector and interest rate have positive contribution to the GDP growth. Only interest and credit by banking sector are significant. The GDP for Chile is significantly but GDP for all other countries are not significantly different from that of Argentina. In this panel data analysis, 25% variation of GDP can be explained by the independent variables considered in the model.
{"title":"Impact of Stock Market, Trade and Bank on Economic Growth for Latin American Countries: An Econometrics Approach","authors":"Md. Shakhawat Hossain, M. Rokonuzzaman","doi":"10.11648/j.sjams.20180601.11","DOIUrl":"https://doi.org/10.11648/j.sjams.20180601.11","url":null,"abstract":"In this study, the impact of stock market, trade and credit by bank on economic growth for nine Latin American countries are examined. Fixed effect panel model with dummy variable approach is used in this research work. Significant Hausman test statistic conferred for fixed effect panel model to analyze this dataset. The inflation rate, import and credit by banking sector have negative impact on GDP growth whereas the rest of the variables, exports, stock market, board money, credit by private sector and interest rate have positive contribution to the GDP growth. Only interest and credit by banking sector are significant. The GDP for Chile is significantly but GDP for all other countries are not significantly different from that of Argentina. In this panel data analysis, 25% variation of GDP can be explained by the independent variables considered in the model.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115590591","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 : 2017-12-07DOI: 10.11648/J.SJAMS.20170506.13
Tesfahun Zewde
This study attempted to assess the factors that lead drivers into traffic accidents at Arba Minch City. 200 drivers were selected using stratified random sampling method and the data have been collected using structured questioners. From sampled drivers 62% of the drivers were involved in one or more accidents. Poisson regression model was the appropriate one compared to the negative binomial regression model for the data. From Poisson regression analysis variables like driver experience, driving after alcohol use, having more licenses, speedy driving, and number of punishments were the causes that lead drivers into traffic accidents in the study area. Road safety professionals should target these factors in their efforts to reduce the occurrence of traffic accidents.
{"title":"Determinants that Lead Drivers into Traffic Accidents: A Case of Arba Minch City, South Ethiopia","authors":"Tesfahun Zewde","doi":"10.11648/J.SJAMS.20170506.13","DOIUrl":"https://doi.org/10.11648/J.SJAMS.20170506.13","url":null,"abstract":"This study attempted to assess the factors that lead drivers into traffic accidents at Arba Minch City. 200 drivers were selected using stratified random sampling method and the data have been collected using structured questioners. From sampled drivers 62% of the drivers were involved in one or more accidents. Poisson regression model was the appropriate one compared to the negative binomial regression model for the data. From Poisson regression analysis variables like driver experience, driving after alcohol use, having more licenses, speedy driving, and number of punishments were the causes that lead drivers into traffic accidents in the study area. Road safety professionals should target these factors in their efforts to reduce the occurrence of traffic accidents.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127362222","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 : 2017-11-11DOI: 10.11648/j.sjams.20170506.12
Wambua Alex Mwaniki, Koske Joseph, Mutiso John, M. Wellington, K. Catherine, Eboi Bramuel
The Agriculture sector is the main stay of the Kenyan economic development contributing over 70% of the Gross Domestic Product (GDP). The sector is faced with numerous challenges leading to frequent and recurrent food shortages. Declining maize grain yield is one among the major challenges that call for urgent interventions to address the looming food crisis in the country. Maize play a big role in the Kenyan food security and in most case lack of the same is taken to mean food insecurity. It is due the importance attached to the crop that a Long Term Agricultural Experiments (LTAE) was set up specifically to research on the Maize grain yield. Many paper published on the LTAE in the country are only single factors analysis and lack the application of Response Surface Methodology (RSM) approaches in solving challenges facing the low and declining maize grain yield ( y 1 ), total microbe population ( y 2 ) a crucial component of Soil Organic Matter (SOM) and their optimization. The focus of this paper therefore is the application of RSM in maize grain yield and total microbial population optimization. Specifically, the paper determined the most significant factors for maize grain yield and total microbial population (bacteria, fungi, actinomycetes, rhizobia), (screening phase of the paper), constructed of an efficient and appropriate experimental design for evaluating the optimal settings of maize yield and total microbial population count and determined univariate optimal settings for maize grain yield and total microbial population. The primary data was summarized from LTAE in National Agricultural Research Laboratories (NARL) in Kabete under the Kenya Agriculture and Livestock Research Organization (KALRO) and secondary data imputed for experimental points falling outside the set field experimental design points. Two treatment factors were identified as the most significant treatment factors (Farm Yard Manure (FYM) and Nitrogen and Phosphorus (NP)) at their low levels and Circumscribed Central Composite Design (CCCD) with two star points as the most efficient design. CCCD passed most optimal criteria of DAET. Univariately, optimal setting for maize grain yield was realized at 3.8x10 3 kg/ha and that of the total microbial population at 3.6x10 6 count. The study confirmed that it was possible to optimize the input treatment factor that lead to the optimization of both maize grain yield and maintaining maximal total microbial population count at its optimal levels.
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