Sustainable Statistical and Data Science Methods and Practices
portes grátis
Sustainable Statistical and Data Science Methods and Practices
Reports from LISA 2020 Global Network, Ghana, 2022
Vance, Eric A.; Awe, O. Olawale
Springer International Publishing AG
01/2024
415
Dura
Inglês
9783031413513
15 a 20 dias
Descrição não disponível.
Chapter. 1. Using social media and network services to promote statistical collaboration laboratories: A case study of LEA Brazil.- Chapter. 2. Renewable Energy Forecasting Using Deep Learning Models.- Chapter. 3. Exploring feature selection and supervised classification algorithms for predicting Obesity among rural women for policy decisions.- Chapter. 4. Re-examining Inflation and its drivers in Nigeria: A machine learning approach.- Chapter. 5. Estimating Relative Response Rates and Preferential Ranking of Subjects.- Chapter. 6. Wealth Creation and Poverty Alleviation in a Nigerian State: A Recent Evidence-Based Survey.- Chapter. 7. Effect of Statistics on Collaboration for Enhancing Institutional Sustainability: A Case of Mzumbe University-Tanzania.- Chapter. 8. Strategies for the Sustainability of Stat Labs: A Case Study of Laboratory of Interdisciplinary Statistical Analysis, Lahore College for Women University Lahore, Pakistan (LISA-LCWU).- Chapter. 9. Advanced Mathematics and Computations for Innovation and Sustainability of Modern Statistics Laboratory.- Chapter. 10. A New Estimator for the GPD Parameters under the POT Approach.- Chapter. 11. A simple yet Robust Estimation of binned data: Egypt Income distribution and Geographical Inequality.- Chapter. 12. Supervised Machine Learning Classification Algorithms: Some Applications and Code Snippets for Practical Implementations in Python Programming.- Chapter. 13. Exploring the spatial variability and different determinants of co-existence of under-nutritional status among children in India through a Bayesian geo-additive multinomial regression model.- Chapter. 14. Predicting the Nature of Terrorist Attacks in Nigeria Using Bayesian Neural Network Model.- Chapter. 15. Salvage Value from Deterioration (SVD): An Optimal Inventory Model for Chicken Egg Marketing.- Chapter. 16. Structural Equation Modeling with Stata: Illustration using a Population-Based, Nationally-Representative Dataset.- Chapter. 17. Time series forecasting of seasonal non-stationary climate data: A comparative study.- Chapter. 18. Weighted Hard and Soft Voting Ensemble Machine Learning CLASIFIERS: Application to Anaemia Diagnosis.- Chapter 19. Machine Learning Approaches for Handling Imbalances in Health Data Classification.- Chapter. 20. The Intersection of Data and Statistics with Sustainable Development Goals.- Chapter. 21. Teaching Data Science in Africa via Online Team-Based Learning.
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Conference Proceedings;Research;Applications;Statistical analysis;Statistics lab;LISA 2020;Data science education;Interdisciplinary statistical analysis;SDG;Data science;Statistics education
Chapter. 1. Using social media and network services to promote statistical collaboration laboratories: A case study of LEA Brazil.- Chapter. 2. Renewable Energy Forecasting Using Deep Learning Models.- Chapter. 3. Exploring feature selection and supervised classification algorithms for predicting Obesity among rural women for policy decisions.- Chapter. 4. Re-examining Inflation and its drivers in Nigeria: A machine learning approach.- Chapter. 5. Estimating Relative Response Rates and Preferential Ranking of Subjects.- Chapter. 6. Wealth Creation and Poverty Alleviation in a Nigerian State: A Recent Evidence-Based Survey.- Chapter. 7. Effect of Statistics on Collaboration for Enhancing Institutional Sustainability: A Case of Mzumbe University-Tanzania.- Chapter. 8. Strategies for the Sustainability of Stat Labs: A Case Study of Laboratory of Interdisciplinary Statistical Analysis, Lahore College for Women University Lahore, Pakistan (LISA-LCWU).- Chapter. 9. Advanced Mathematics and Computations for Innovation and Sustainability of Modern Statistics Laboratory.- Chapter. 10. A New Estimator for the GPD Parameters under the POT Approach.- Chapter. 11. A simple yet Robust Estimation of binned data: Egypt Income distribution and Geographical Inequality.- Chapter. 12. Supervised Machine Learning Classification Algorithms: Some Applications and Code Snippets for Practical Implementations in Python Programming.- Chapter. 13. Exploring the spatial variability and different determinants of co-existence of under-nutritional status among children in India through a Bayesian geo-additive multinomial regression model.- Chapter. 14. Predicting the Nature of Terrorist Attacks in Nigeria Using Bayesian Neural Network Model.- Chapter. 15. Salvage Value from Deterioration (SVD): An Optimal Inventory Model for Chicken Egg Marketing.- Chapter. 16. Structural Equation Modeling with Stata: Illustration using a Population-Based, Nationally-Representative Dataset.- Chapter. 17. Time series forecasting of seasonal non-stationary climate data: A comparative study.- Chapter. 18. Weighted Hard and Soft Voting Ensemble Machine Learning CLASIFIERS: Application to Anaemia Diagnosis.- Chapter 19. Machine Learning Approaches for Handling Imbalances in Health Data Classification.- Chapter. 20. The Intersection of Data and Statistics with Sustainable Development Goals.- Chapter. 21. Teaching Data Science in Africa via Online Team-Based Learning.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
