Book description
Commissioned by the Statistical Society of Canada (SSC), this volume helps both general readers and users of statistics better appreciate the scope and importance of statistics. It presents the ways in which statistics is used while highlighting key contributions that Canadian statisticians are making to science, technology, business, government, and other areas. The book emphasizes the role and impact of computing in statistical modeling and analysis, including the issues involved with the huge amounts of data being generated by automated processes.
Table of contents
- Front Cover
- Contents (1/2)
- Contents (2/2)
- Foreword
- Preface
- About the Editor
- Contributors
- Chapter 1: Canadians Studying Abroad and the Development of Statistics in Canada (1/4)
- Chapter 1: Canadians Studying Abroad and the Development of Statistics in Canada (2/4)
- Chapter 1: Canadians Studying Abroad and the Development of Statistics in Canada (3/4)
- Chapter 1: Canadians Studying Abroad and the Development of Statistics in Canada (4/4)
- Chapter 2: Some of Statistics Canada’s Contributions to Survey Methodology (1/6)
- Chapter 2: Some of Statistics Canada’s Contributions to Survey Methodology (2/6)
- Chapter 2: Some of Statistics Canada’s Contributions to Survey Methodology (3/6)
- Chapter 2: Some of Statistics Canada’s Contributions to Survey Methodology (4/6)
- Chapter 2: Some of Statistics Canada’s Contributions to Survey Methodology (5/6)
- Chapter 2: Some of Statistics Canada’s Contributions to Survey Methodology (6/6)
- Chapter 3: Watching Children Grow Taught Us All We Know (1/3)
- Chapter 3: Watching Children Grow Taught Us All We Know (2/3)
- Chapter 3: Watching Children Grow Taught Us All We Know (3/3)
- Chapter 4: Modeling Dependence beyond Correlation (1/4)
- Chapter 4: Modeling Dependence beyond Correlation (2/4)
- Chapter 4: Modeling Dependence beyond Correlation (3/4)
- Chapter 4: Modeling Dependence beyond Correlation (4/4)
- Chapter 5: Lasso and Sparsity in Statistics (1/3)
- Chapter 5: Lasso and Sparsity in Statistics (2/3)
- Chapter 5: Lasso and Sparsity in Statistics (3/3)
- Chapter 6: Optimizing and Adapting the Metropolis Algorithm (1/4)
- Chapter 6: Optimizing and Adapting the Metropolis Algorithm (2/4)
- Chapter 6: Optimizing and Adapting the Metropolis Algorithm (3/4)
- Chapter 6: Optimizing and Adapting the Metropolis Algorithm (4/4)
- Chapter 7: Design of Computer Experiments for Optimization, Estimation of Function Contours, and Related Objectives (1/4)
- Chapter 7: Design of Computer Experiments for Optimization, Estimation of Function Contours, and Related Objectives (2/4)
- Chapter 7: Design of Computer Experiments for Optimization, Estimation of Function Contours, and Related Objectives (3/4)
- Chapter 7: Design of Computer Experiments for Optimization, Estimation of Function Contours, and Related Objectives (4/4)
- Chapter 8: Statistical Genetic Modeling and Analysis of Complex Traits (1/5)
- Chapter 8: Statistical Genetic Modeling and Analysis of Complex Traits (2/5)
- Chapter 8: Statistical Genetic Modeling and Analysis of Complex Traits (3/5)
- Chapter 8: Statistical Genetic Modeling and Analysis of Complex Traits (4/5)
- Chapter 8: Statistical Genetic Modeling and Analysis of Complex Traits (5/5)
- Chapter 9: Bayesian Methods in Fisher’s Statistical Genetics World (1/4)
- Chapter 9: Bayesian Methods in Fisher’s Statistical Genetics World (2/4)
- Chapter 9: Bayesian Methods in Fisher’s Statistical Genetics World (3/4)
- Chapter 9: Bayesian Methods in Fisher’s Statistical Genetics World (4/4)
- Chapter 10: Bayesian Statistical Methodology for Observational Health Sciences Data (1/3)
- Chapter 10: Bayesian Statistical Methodology for Observational Health Sciences Data (2/3)
- Chapter 10: Bayesian Statistical Methodology for Observational Health Sciences Data (3/3)
- Chapter 11: Statistical Models for Disease Processes:Markers and Skeletal Complications in Cancer Metastatic to Bone (1/4)
- Chapter 11: Statistical Models for Disease Processes:Markers and Skeletal Complications in Cancer Metastatic to Bone (2/4)
- Chapter 11: Statistical Models for Disease Processes:Markers and Skeletal Complications in Cancer Metastatic to Bone (3/4)
- Chapter 11: Statistical Models for Disease Processes:Markers and Skeletal Complications in Cancer Metastatic to Bone (4/4)
- Chapter 12: Analysis of Biased Survival Data: The Canadian Study of Health and Aging andbeyond (1/4)
- Chapter 12: Analysis of Biased Survival Data: The Canadian Study of Health and Aging andbeyond (2/4)
- Chapter 12: Analysis of Biased Survival Data: The Canadian Study of Health and Aging andbeyond (3/4)
- Chapter 12: Analysis of Biased Survival Data: The Canadian Study of Health and Aging andbeyond (4/4)
- Chapter 13: Assessing the Effect on Survival of Kidney Transplantation with Higher-Risk Donor Kidneys (1/4)
- Chapter 13: Assessing the Effect on Survival of Kidney Transplantation with Higher-Risk Donor Kidneys (2/4)
- Chapter 13: Assessing the Effect on Survival of Kidney Transplantation with Higher-Risk Donor Kidneys (3/4)
- Chapter 13: Assessing the Effect on Survival of Kidney Transplantation with Higher-Risk Donor Kidneys (4/4)
- Chapter 14: Risk-Adjusted Monitoring of Outcomes in Health Care (1/4)
- Chapter 14: Risk-Adjusted Monitoring of Outcomes in Health Care (2/4)
- Chapter 14: Risk-Adjusted Monitoring of Outcomes in Health Care (3/4)
- Chapter 14: Risk-Adjusted Monitoring of Outcomes in Health Care (4/4)
- Chapter 15: Statistics in Financial Engineering (1/4)
- Chapter 15: Statistics in Financial Engineering (2/4)
- Chapter 15: Statistics in Financial Engineering (3/4)
- Chapter 15: Statistics in Financial Engineering (4/4)
- Chapter 16: Making Personalized Recommendations in E-Commerce (1/2)
- Chapter 16: Making Personalized Recommendations in E-Commerce (2/2)
- Chapter 17: What Do Salmon and Injection Drug Users Have in Common? (1/4)
- Chapter 17: What Do Salmon and Injection Drug Users Have in Common? (2/4)
- Chapter 17: What Do Salmon and Injection Drug Users Have in Common? (3/4)
- Chapter 17: What Do Salmon and Injection Drug Users Have in Common? (4/4)
- Chapter 18: Capture–Recapture Methods for Estimating the Size of a Population: Dealing with Variable Capture Probabilities (1/4)
- Chapter 18: Capture–Recapture Methods for Estimating the Size of a Population: Dealing with Variable Capture Probabilities (2/4)
- Chapter 18: Capture–Recapture Methods for Estimating the Size of a Population: Dealing with Variable Capture Probabilities (3/4)
- Chapter 18: Capture–Recapture Methods for Estimating the Size of a Population: Dealing with Variable Capture Probabilities (4/4)
- Chapter 19: Challenges in Statistical Marine Ecology (1/4)
- Chapter 19: Challenges in Statistical Marine Ecology (2/4)
- Chapter 19: Challenges in Statistical Marine Ecology (3/4)
- Chapter 19: Challenges in Statistical Marine Ecology (4/4)
- Chapter 20: Quantifying the Human and Natural Contributions to Observed Climate Change (1/4)
- Chapter 20: Quantifying the Human and Natural Contributions to Observed Climate Change (2/4)
- Chapter 20: Quantifying the Human and Natural Contributions to Observed Climate Change (3/4)
- Chapter 20: Quantifying the Human and Natural Contributions to Observed Climate Change (4/4)
- Chapter 21: Data Hungry Models in a Food Hungry World: An Interdisciplinary Challenge Bridged by Statistics (1/4)
- Chapter 21: Data Hungry Models in a Food Hungry World: An Interdisciplinary Challenge Bridged by Statistics (2/4)
- Chapter 21: Data Hungry Models in a Food Hungry World: An Interdisciplinary Challenge Bridged by Statistics (3/4)
- Chapter 21: Data Hungry Models in a Food Hungry World: An Interdisciplinary Challenge Bridged by Statistics (4/4)
- Back Cover
Product information
- Title: Statistics in Action
- Author(s):
- Release date: March 2014
- Publisher(s): Chapman and Hall/CRC
- ISBN: 9781482236248
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