Khushnoor Khan

Determining the impact of age and LOS on job satisfaction: a case study of Pakistan automotive industry

This research was conducted to ascertain the impact of age and length of service (LOS) on job satisfaction in engineers of Pakistan public sector. Field survey was conducted using job satisfaction survey (JSS) questionnaire having closed-ended questions. Multistage sampling was conducted using a combination of cluster sampling, stratified sampling and random sampling techniques. Power and Precision software was used to determine the sample size. JSS questionnaires were administered amongst 225 electrical and mechanical engineers from five public sector organizations. 158 usable questionnaires were received and data were analyzed in SPSS. Statistical analyses showed existence of an open mouth U-shaped relationship between LOS/age and job satisfaction. It was found that age moderates relationship between LOS and job satisfaction. Non-responsiveness of senior engineers led to one of the limitations of this study. Results of this study can be used for policy-making decisions.

A Time Truncated Moving Average Chart for the Weibull Distribution

A control chart of monitoring the number of failures is proposed with a moving average scheme, when the life of an item follows a Weibull distribution. A specified number of items are put on a time truncated life test and the number of failures is observed. The proposed control chart has been evaluated by the average run lengths (ARLs) under different parameter settings. The control constant and the test time multiplier are to be determined by considering the in-control ARL. It is observed that the proposed control chart is more efficient in detecting a shift in the process as compared with the existing time truncated control chart.

Personality Traits as Predictor of Emotional Intelligence among the University Teachers as Advisors

The focus of the present study was to investigate personality traits as the predictor of emotional intelligence (EI) among the university teachers working as student advisors. A sample of the study comprised 100 student advisors (male = 50; female = 50). The age range of the sample was 21–40 years. Schutte Emotional Intelligence Scale (SEIS) and Big Five Inventory (BFI) were used to measure emotional intelligence (EI) and personality traits. For the statistical analysis of the data, -test and regression analysis were computed. The findings revealed that three personality traits, extraversion, agreeableness, and openness to experience, emerged as significant predictors of EI. The findings also revealed that conscientiousness and neuroticism have no impact on EI. -tests indicated that there are no gender differences in EI. Considering the implication of personality traits on EI among university teachers/student advisors, the current research may assist in augmenting the organizational behavior in general and boost the productivity in particular which are both essential ingredients for the deliverance of services to all the stakeholders linked with the educational system in Saudi Arabia.

Comparisons of decision tree methods using water data

ABSTRACT This article demonstrates the application of classification trees (decision trees), logistic regression (LR), and linear discriminant function (LDR) to classify data of water quality (i.e., whether the water is fit for drinking on not fit for drinking). The data on water quality were obtained from Pakistan Council of Research in Water Resources (PCRWR) for two cities of Pakistan—one representing industrial environment (Sialkot) and the other one representing non-industrial environment (Narowal). To classify data on water quality, three statistical tools were employed—the Decision Tree methodology using Gini Index, LR, and LDA—using R software library. The results obtained by the said three techniques were compared using misclassification rates (a model with minimum value of misclassification rate is better). It was witnessed that LR performed well than the other two techniques while the Decision trees and LDA performed equally well. But for illustration purposes decision trees technique is comparatively easy to draw and interpret.