04339nam 2200577 450 991049515830332120230503131743.0981-16-1919-010.1007/978-981-16-1919-9(CKB)4100000011999113(DE-He213)978-981-16-1919-9(MiAaPQ)EBC6700088(Au-PeEL)EBL6700088(PPN)257355871(EXLCZ)99410000001199911320220428d2021 uy 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierData science and SDGs challenges, opportunities and realities /Bikas Kumar Sinha, Nurul Haque Mollah, editors1st ed. 2021.Singapore :Springer,[2021]©20211 online resource (XXII, 197 p. 45 illus., 32 illus. in color.)981-16-1918-2 Chapter 1: SDGs in Bangladesh: Implementation Challenges & Way Forward -- Chapter 2: Some Models and Their Extensions for Longitudinal Analyses -- Chapter 3: Association of IL-6 Gene rs1800796 Polymorphism with Cancer Risk: A Meta-Analysis -- Chapter 4: Two Level Logistic Regression Analysis of Factors Influencing Dual form of Malnutrition in Mother-child Pairs: A Household Study in Bangladesh -- Chapter 5: Divide and Recombine Approach for Analysis of Failure Data Using Parametric Regression Model -- Chapter 6: Performance of different data mining methods for predicting rainfall of Rajshahi district, Bangladesh -- Chapter 7: Generalized Vector Auto-regression Controlling Intervention and Volatility for Climatic Variables -- Chapter 8: Experimental Designs for fMRI Studies in Small Samples -- Chapter 9: Bioinformatic Analysis of Differentially Expressed Genes (DEGs) Detected from RNA-Sequencing Profiles of Mouse Striatum -- Chapter 10: Level of Serum High-sensitivity C-reactive protein Predicts Atherosclerosis and Coronary Artery Disease in Hyperglycemic Patients -- Chapter 11: Identification of Outliers in Gene Expression Data -- Chapter 12: Selecting Covariance Structure to Analyze Longitudinal Data: A Study to Model the Body Mass Index of Primary School Going Children in Bangladesh -- Chapter 13: Statistical Analysis of Various Optimal Latin Hypercube Designs -- Chapter 14: Erlang Loss Formulas: An Elementary Derivation -- Chapter 15: Machine Learning, Regression and Numerical Optimization.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 7th 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.EstadísticathubEconomiathubDesenvolupament sosteniblethubEconomicsStatistical methodsCongressesSustainable developmentStatistical methodsCongressesCongressosthubLlibres electrònicsthubEstadísticaEconomiaDesenvolupament sostenibleEconomicsStatistical methodsSustainable developmentStatistical methods330.015195Sinha Bikas KumarMollah Nurul HaqueMiAaPQMiAaPQMiAaPQBOOK9910495158303321Data Science and SDGs1894578UNINA