Statistics for Data Science and Policy Analysis

1. Front Matter

   Pages i-xv

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2. Applied Statistics and Bayesian Modeling

   1. Front Matter

      Pages 1-1

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   2. Applied Bayesian Modeling for Assessment of Interpretation Uncertainty in Spatial Domains

      • Scott McManus, Azizur Rahman, Ana Horta, Jacqueline Coombes

      Pages 3-13

   3. Computing Robust Statistics via an EM Algorithm

      • Maheswaran Rohan

      Pages 15-26

   4. Determining Risk Factors of Antenatal Care Attendance and its Frequency in Bangladesh: An Application of Count Regression Analysis

      • Kakoli Rani Bhowmik, Sumonkanti Das, Md. Atiqul Islam

      Pages 27-39

   5. On Propensity Score Methodology

      • Paul Dewick, Shuangzhe Liu

      Pages 41-53

   6. Asking Good Questions to Understand Voluntary Enrolments in Mathematics

      • Ning Li

      Pages 55-70

3. Agricultural Statistics and Policy Analysis

   1. Front Matter

      Pages 71-71

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   2. Modeling for Prospect of Aman Rice Production in Dhaka Division, Bangladesh

      • Sayed Mohibul Hossen, Md. Takrib Hossain, Aditi Chakraborty, Mohd Tahir Ismail

      Pages 73-85

   3. Impacts and Determinants of Adoption in River-Based Tilapia Cage Culture

      • Mohammad Mizanul Haque Kazal, Md. Sadique Rahman

      Pages 87-95

   4. Policy into Practice; Statistics the Forgotten Gatekeeper

      • Iain H. Hume

      Pages 97-109

   5. Nutrient Loading in the River Systems Around Major Cities in Bangladesh: A Quantitative Estimate with Consequences and Potential Recycling Options

      • Shamim Mia, Md. Rushna Alam, Md. Abdus Sattar, Feike A. Dijkstra

      Pages 111-128

   6. Analysing Informal Milk Supply Chains Data to Identify Seasonal Occurrences of Antibiotic Residues

      • Naveed Aslam, Sosheel S. Godfrey, Mateen Abbas, Muhammad Y. Tipu, Muhammad Ishaq, David M. McGill et al.

      Pages 129-142

4. Data Science and Image Processing Statistics

   1. Front Matter

      Pages 143-143

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   2. Detection of Vegetation in Environmental Repeat Photography: A New Algorithmic Approach in Data Science

      • Asim Khan, Anwaar Ulhaq, Randall Robinson, Mobeen Ur Rehman

      Pages 145-157

   3. Can Data Fusion Increase the Performance of Action Detection in the Dark?

      • Anwaar Ulhaq

      Pages 159-171

   4. Data Privacy and Security in the Cloud

      • Peter Padiet, Md. Rafiqul Islam, Azizur Rahman

      Pages 173-183

   5. Evaluating Faster-RCNN and YOLOv3 for Target Detection in Multi-sensor Data

      • Anwaar Ulhaq, Asim Khan, Randall Robinson

      Pages 185-193

   6. Wavelet-Based Quantile Density Function Estimation Under Random Censorship

      • Esmaeil Shirazi, Hassan Doosti

      Pages 195-204

5. Health Statistics and Social Policy

   1. Front Matter

      Pages 205-205

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This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. Written by leading international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.

• Applied statistics
• Business statistics
• Bayesian modelling
• Computational statistics
• Health statistics
• Multivariate statistics
• Research methodology
• Social statistics
• Artificial intelligence
• Big data analytics
• Business analytics
• Data mining
• Data science
• Image processing
• Microdata analysis
• Microsimulation modelling

• School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, Australia

  Azizur Rahman

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.

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