Statistics for Data Science and Policy Analysis

Part I. Applied Statistics and Bayesian Modeling.- 1. Applied Bayesian Modeling for Assessment of Interpretation Uncertainty in Spatial Domain.- 2. Computing Robust Statistics via an EM Algorithm.- 3. Determining Risk Factors of Antenatal Care Attendance and its Frequency in Bangladesh: An Application of Count Regression Analysis.- 4. On Propensity Score Methodology.- 5. Asking Good Questions to Understand Voluntary Enrolments in Mathematics.- PART II. Agricultural Statistics and Policy Analysis.- 6. Modeling for Prospect of Aman Rice Production in Dhaka Division, Bangladesh.- 7. Impacts and Determinants of Adoption in River-based Tilapia Cage Culture.- 8. Policy into Practice; Statistics the Forgotten Gatekeeper.- 9. Nutrient Loading in the River Systems around Major Cities in Bangladesh: a Quantitative Estimate with Consequences and Potential Recycling Options.- 10. Analysing Informal Milk Supply Chains Data to Identify Seasonal Occurrences of Antibiotic Residues.- Part III. Data Science and Image Processing Statistics.- 11. Detection of Vegetation in Enviromental Repeat Photography: A New Algorithmic Approach in Data Science.- 12. Can Data Fusion increase the Performance of Action Detection in the Dark?.- 13. Data privacy and Security in the Cloud.- 14. Evaluating Faster-RCNN and YOLOv3 for Target Detection in Multi-sensor Data.- 15. Wavelet-based Quantile Density Function Estimation under Random Censorship.- Part IV. Health Statistics and Social Policy.- 16. Factors Associated with Coronary Heart Disease among Elderly People in Different Communities.- 17. Finite Mixture Modelling Approach to Identify Factors Affecting Children ever Born for 15-49 Year Old Women in Asian Country.- 18. An Assessment of Influencing Factors for Motherhood During Childhood in Bangladesh Using Factor Analysis and Logistic Regression Methods.- 19. Effect of Women's Education on Skilled Birth Attendants in South and South East Asia: A Cross-country assessment on Sustainable

Associate Professor Azizur Rahman, PhD, is an applied statistician and data scientist with expertise in both developing and applying novel methodologies, models and technologies. He is the Leader of "Statistics and Data Mining Research Group" in the Faculty of Business, Justice and Behavioural Sciences at the Charles Sturt University (CSU). Prof. Rahman is able to assist in understanding multi-disciplinary research issues within various fields including how to understand the individual activities which occur within very complex scientific, behavioural, socio-economic and ecological systems.He develops "alternative methods in microsimulation modelling technologies" which are very useful tools to socioeconomic policy analysis and evaluation. His 2016 book has contributed significantly to the field of small area estimation and microsimulation modelling. Prof. Rahman's research interests encompass issues in simple to multi-facet analyses in various fields ranging from the mathematical sciences to the law and legal studies. He has more than 100 scholarly publications including a few books. Prof. Rahman's research is funded by the Australian Federal and State Governments, and he serves on a range of editorial boards including the International Journal of Microsimulation (IJM) and Sustaining Regions. He obtained several awards including the SOCM Research Excellence Award 2018 and the CSU-RED Achievement Award 2019.