Asian Journal of Probability and Statistics <p style="text-align: justify;"><strong>Asian Journal of Probability and Statistics (ISSN: 2582-0230)</strong> aims to publish high-quality papers (<a href="/index.php/AJPAS/general-guideline-for-authors">Click here for Types of paper</a>) in all areas of ‘Probability and Statistics’. By not excluding papers on the basis of novelty, this journal facilitates the research and wishes to publish papers as long as they are technically correct and scientifically motivated. The journal also encourages the submission of useful reports of negative results. This is a quality controlled, OPEN peer-reviewed, open access INTERNATIONAL journal.</p> en-US (Asian Journal of Probability and Statistics) (Asian Journal of Probability and Statistics) Sun, 25 Oct 2020 03:25:45 +0000 OJS 60 Scholarly Book Review on Bayesian Statistics for Beginners: A Step-by-Step Approach <p>This book offers the students and researchers a unique introduction to Bayesian statistics. Authors provide a wonderful journey in the realm of Bayesian Probability and aspire readers to become Bayesian statisticians. The book starts with Introduction to Probability and covers Bayes’ Theorem, Probability Mass Functions, Probability Density Functions, The Beta-Binomial Conjugate, Markov chain Monte Carlo (MCMC), and Metropolis-Hastings Algorithm. The book is very well written, and topics are very to the point with real-world applications but does not provide examples for computing using common open-source software.</p> Eahsan Shahriary, Amir Hajibabaee ##submission.copyrightStatement## Sun, 25 Oct 2020 00:00:00 +0000 Professional Development Needs to Improve Teaching Science in Secondary Schools: Case Study of Mbeya, Tanzania <p><strong>Aim: </strong>This study examined pedagogy and subject content needs for Professional Development (PD) to improve teachers’ skills in teaching science in secondary schools in Mbeya, Tanzania.</p> <p><strong>Study Design:</strong> The study employed a quantitative research approach and cross-sectional survey design.</p> <p><strong>Methodology: </strong>The main instrument used for the study was questionnaire. In this study, schools were randomly selected, and 256 respondents, science teachers were selected through stratified sampling technique. The data collected were analyzed quantitatively.</p> <p><strong>Results: </strong>Science teachers need Professional Development (PD) in Pedagogical Knowledge (PK), masterly of science subject contents and technological skills of modern teaching. There was no significant difference in the mean scores for components of pedagogy knowledge between teachers who teach math subject and those who teach physics, chemistry and biology at &nbsp;using independent samples t-test. Teachers need of PD in subject content in topics were as follows: accounts (61.7%), genetics (46.2%), electromagnetism (44.2%), electronics (40.4%), circles and the Earth as a sphere (29.6%), statistics and probability (28.4%), inorganic chemistry (25%), and ionic theory and electrolysis (24.1%).</p> <p><strong>Conclusion: </strong>Science and mathematics teachers in Secondary schools need PD intervention in the subject content of science subjects.</p> Charles Ephraim Kibona, Joyce Sifa Ndabi, Isack Ephraim Kibona ##submission.copyrightStatement## Mon, 26 Oct 2020 00:00:00 +0000 A New Generalized Weibull- Odd Frѐchet Family of Distributions: Statistical Properties and Applications <p>We introduced a new generalized Weibull- Odd Frѐchet family of distributions with three extra parameters and we derived some of its structural properties. We derived comprehensive mathematical properties which include moments, moment generating function, Entropies and Order Statistics. One family of this distribution called new generalized Weibull- Odd Frѐchet -Frѐchet distribution is used to fit two data sets using the MLE procedure. A Monte Carlo simulation is used to test the robustness of the parameters of this distribution, in terms of the bias and mean squared error. The results of fitting this new distribution to two different data sets suggest that the new distribution outperforms its competitors.</p> A. Usman, S. I. S. Doguwa, B. B. Alhaji, A. T. Imam ##submission.copyrightStatement## Sun, 25 Oct 2020 00:00:00 +0000