Data Science and SDGs: Challenges, Opportunities and Realities

by Bikas Kumar Sinha, Md. Nurul Haque Mollah

Length: 219 pages
Edition: 1
Language: English
Publisher: Springer
Publication Date: 2021-08-14
ISBN-10: 9811619182
ISBN-13: 9789811619182
Sales Rank: #0 (See Top 100 Books)

The book presents contributions on statistical models and methods applied, for both data science and SDGs, in one place. Measuring and controlling data of SDGs, data driven measurement of progress needs to be distributed to stakeholders. In this situation, the techniques used in data science, specially, in the big data analytics, play an important role rather than the traditional data gathering and manipulation techniques. This book fills this space through its twenty contributions. The contributions have been selected from those presented during the 7^th International Conference on Data Science and Sustainable Development Goals organized by the Department of Statistics, University of Rajshahi, Bangladesh; and cover topics mainly on SDGs, bioinformatics, public health, medical informatics, environmental statistics, data science and machine learning.

The contents of the volume would be useful to policymakers, researchers, government entities, civil society, and nonprofit organizations for monitoring and accelerating the progress of SDGs.

Cover
Front Matter
SDGs in Bangladesh: Implementation Challenges and Way Forward
Some Models and Their Extensions for Longitudinal Analyses
Association of IL-6 Gene rs1800796 Polymorphism with Cancer Risk: A Meta-Analysis
Two Level Logistic Regression Analysis of Factors Influencing Dual Form of Malnutrition in Mother–Child Pairs: A Household Study in Bangladesh
Divide and Recombine Approach for Analysis of Failure Data Using Parametric Regression Model
Performance of Different Data Mining Methods for Predicting Rainfall of Rajshahi District, Bangladesh
Generalized Vector Autoregression Controlling Intervention and Volatility for Climatic Variables
Experimental Designs for fMRI Studies in Small Samples
Bioinformatic Analysis of Differentially Expressed Genes (DEGs) Detected from RNA-Sequence Profiles of Mouse Striatum
Role of Serum High-Sensitivity C-Reactive Protein Level as Risk Factor in the Prediction of Coronary Artery Disease in Hyperglycemic Subjects
Identification of Outliers in Gene Expression Data
Selecting Covariance Structure to Analyze Longitudinal Data: A Study to Model the Body Mass Index of Primary School-Going Children in Bangladesh
Statistical Analysis of Various Optimal Latin Hypercube Designs
Erlang Loss Formulas: An Elementary Derivation
Machine Learning, Regression and Optimization