© 2020

Statistics for Data Science and Policy Analysis

  • Azizur Rahman
Conference proceedings

Table of contents

  1. Front Matter
    Pages i-xv
  2. Applied Statistics and Bayesian Modeling

    1. Front Matter
      Pages 1-1
    2. Scott McManus, Azizur Rahman, Ana Horta, Jacqueline Coombes
      Pages 3-13
    3. Paul Dewick, Shuangzhe Liu
      Pages 41-53
  3. Agricultural Statistics and Policy Analysis

    1. Front Matter
      Pages 71-71
    2. Sayed Mohibul Hossen, Md. Takrib Hossain, Aditi Chakraborty, Mohd Tahir Ismail
      Pages 73-85
    3. Mohammad Mizanul Haque Kazal, Md. Sadique Rahman
      Pages 87-95
    4. 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
    2. Asim Khan, Anwaar Ulhaq, Randall Robinson, Mobeen Ur Rehman
      Pages 145-157
    3. Peter Padiet, Md. Rafiqul Islam, Azizur Rahman
      Pages 173-183
    4. Anwaar Ulhaq, Asim Khan, Randall Robinson
      Pages 185-193
  5. Health Statistics and Social Policy

    1. Front Matter
      Pages 205-205

About these proceedings


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

Editors and affiliations

  • Azizur Rahman
    • 1
  1. 1.School of Computing and MathematicsCharles Sturt UniversityWagga WaggaAustralia

About the editors

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.

Bibliographic information