Students’ Survey Evaluation: A New Paradigm

The lynchpin of any educational setup is the duo of student and teacher; the third vital component which regulates the activities of the duo is educational management of the setup. The present study focuses on eliciting the opinions of students from three diplomas organized by Deanship of Community Services and Continuing Education, King Abdulaziz University, Jeddah to study the effectiveness of diplomas. The instrument diploma evaluation questionnaire (DEQ) used to collect data was a modified version of the course evaluation questionnaire (CEQ) developed by the Saudi National commission of Assessment and Academic Accreditation (NCAAA). A sample of 240 diploma students both male and female participated in the study. Statistical evaluation was carried out using SPSS ver 21 and some relevant figures were drawn using AMOS software. Findings of this study coupled with other inputs can simultaneously be used by pedagogical staff and administrators to frame future policies for improving the quality of educational diplomas in an institution or program. Results of the study pinpointed some areas which need to be focused on in future diplomas: for instance, orientation about the diplomas needs more elaboration, provision of training material and linkage between the theory and practice be established. The relationship between the three subscales and Overall Evaluation (OE) is significant with ‘Diploma evaluation’ subscale as the most effective predictor for OE followed by ‘During the diploma’ subscale.  The study also demonstrated the robust evidence of objectivity and data authenticity. The easy-to-follow approach has been adopted so that pedagogical and administrative staff can effectively use the techniques proposed in the current study. The evidence thus extracted can be used to structure efficient prospective policies than can surely enhance student experiences during their educational discourses

Assessing Volatility Modelling using three Error Distributions

The current study focuses on estimating the volatility of stock returns in the presence of flat tails error distribution (i.e. asymmetry of the distribution) which a traditional generalized auto-regressive conditional heteroscedasticity GARCH model usually fails to explain. The study, unlike the previous studies, compares three sets of error distributions for GARCH (1, 1) model of stock returns.  The three sets of error distributions used for comparing the predictive ability of GARCH (1, 1) model are –Gaussian (normal distribution), student’s t and generalized error distribution (GED). Eviews software was used for analyzing a time series data of Flying cement stock shares consisting of 245 days of in sample and 15 days of out-of-sample data. To compare the forecasting capability of three models root mean square (RMSE) and Theil’s Inequality Coefficient (TIC) were used. Akaike information criterion (AIC), the Schwarz information criterion (SIC), Hannan, and Quin (HQ) information criteria were examined for selection of a suitable model for capturing volatility of stock returns in the presence of symmetrical and asymmetrical distributions. Results of the study revealed that GARCH (1, 1) with GED is the best model for capturing the volatility of stock returns of Flying Cement Industry. Results of the present study will provide a stimulus to academia and practitioners for incorporating asymmetry aspect of the distribution in future prediction and capturing volatility of stock returns

Assessing Volatility Modelling using three Error Distributions

The current study focuses on estimating the volatility of stock returns in the presence of flat tails error distribution (i.e. asymmetry of the distribution) which a traditional generalized auto-regressive conditional heteroscedasticity GARCH model usually fails to explain. The study, unlike the previous studies, compares three sets of error distributions for GARCH (1, 1) model of stock returns.  The three sets of error distributions used for comparing the predictive ability of GARCH (1, 1) model are –Gaussian (normal distribution), student’s t and generalized error distribution (GED). Eviews software was used for analyzing a time series data of Flying cement stock shares consisting of 245 days of in sample and 15 days of out-of-sample data. To compare the forecasting capability of three models root mean square (RMSE) and Theil’s Inequality Coefficient (TIC) were used. Akaike information criterion (AIC), the Schwarz information criterion (SIC), Hannan, and Quin (HQ) information criteria were examined for selection of a suitable model for capturing volatility of stock returns in the presence of symmetrical and asymmetrical distributions. Results of the study revealed that GARCH (1, 1) with GED is the best model for capturing the volatility of stock returns of Flying Cement Industry. Results of the present study will provide a stimulus to academia and practitioners for incorporating asymmetry aspect of the distribution in future prediction and capturing volatility of stock returns

Anger and Interpersonal Relationships: Social Life in Adolescence

Around 1.6 million people across the world die due to violent and anger related acts according to World Health Organization (WHO). One out of five people have problems in their interpersonal relationships due to their anger feelings and expressions. Thus it can be stated that anger control and management is required for the improvisation of relations and life in general. The present study investigates the relationship of anger and interpersonal relationships. Moreover it looks into the gender differences on anger and interpersonal relations. Samples of 200 adolescents (100 male and 100 female students of preparatory year program) were selected from King Abdulaziz University, Jeddah. The age range of the participants was 16 to 19 years. Aggression Questionnaire (ASQ) (Arnold Buss and Mark Perry, 1992) and Interpersonal Support Evaluation List (Cohen, Mermestein, & Kmarck, 1985) were used to measure anger and interpersonal relationship respectively.  Correlation analysis revealed that there is a negative relationship between anger and interpersonal relationship. T-test results indicate that males exhibit more anger and anger related behaviors than females. No significant gender differences were found on interpersonal relationships. Implications for the improvement of educational and counseling programs for the management and control of anger among the adolescents are also discussed

Bayesian Estimation for Parameters of Power Function Distribution under Various Priors

Although the idea of Bayesian inference dates back to the late 18th century, its use by statisticians has been rare until recently. But due to advancement in the simulation techniques Bayesian inference and estimation is gaining currency. This paper seeks to focus on the Bayesian estimates of the Power Function distribution using Weibull and Generalized Gamma distributions as priors for the unknown parameters. Furthermore, the statistical performance of the obtained estimators is compared with the Maximum likelihood of Power Function distribution and the Bayesian estimator of Gamma distribution as prior of the unknown parameter. The comparison has been done using Monte Carlo simulation using MSE as yardstick of the comparison. Keywords: Squared error loss function, Bayesian estimator, Prior distribution, Monte Carlo simulation

Multiple Dependent State Sampling-Based Chart Using Belief Statistic under Neutrosophic Statistics

In this paper, a control chart scheme has been introduced for the mean monitoring using gamma distribution for belief statistics using multiple dependent (deferred) state sampling under the neutrosophic statistics. The coefficients of the control chart and the neutrosophic average run lengths have been estimated for specific false alarm probabilities under various process conditions. The offered chart has been compared with the existing classical chart through simulation and the real data. From the comparison, it is concluded that the performance of the proposed chart is better than that of the existing chart in terms of average run length under uncertain environment. The proposed chart has the ability to detect a shift quickly than the existing chart. It has been observed that the proposed chart is efficient in quick monitoring of the out-of-control process and a cherished addition in the toolkit of the quality control personnel

Design of a New Synthetic Acceptance Sampling Plan

In this paper, we propose a new synthetic sampling plan assuming that the quality characteristic follows the normal distribution with known and unknown standard deviation. The proposed plan is given and the operating characteristic (OC) function is derived to measure the performance of the proposed sampling plan for some fixed parameters. The parameters of the proposed sampling plan are determined using non-linear optimization solution. A real example is added to explain the use of the proposed plan by industry

Acceptance Sampling Plans for Finite and Infinite Lot Size under Power Lindley Distribution

In this paper, we have developed single and double acceptance sampling plans when the product life length follows the power Lindley distribution. The sampling plans have been developed by assuming infinite and finite lot sizes. We have obtained the operating characteristic curves for the resultant sampling plans. The sampling plans have been obtained for various values of the parameters. It has been found that for a finite lot size, the sampling plans provide smaller values of the parameters to achieve the specified acceptance probabilities