This paper examines the associations between clinical dementia and underlying cause of death (UCD) in a population-based sample of seniors who took part in the Canadian Study of Health and Aging (CSHA). Cause-of-death data were obtained via death certificates for 2,924 of 2,982 deceased subjects. Among the decedents were 823 clinically demented and 670 clinically non-demented participants. Using logistic regression we examined factors associated with a particular UCD in the overall group and also in the subgroup of demented seniors. Dementia was found to be associated with an increased risk of death from pneumonia. Both Alzheimer’s disease and vascular dementia appear to decrease the risk of mortality from neoplasm. To our knowledge, this study is the first of its kind that combines a large, representative sample with thorough clinical assessment of cognitive status.

Modern data and applications pose very different challenges from those of the 1950s or even the 1980s. Students contemplating a career in statistics or data science need to have the tools to tackle problems involving massive, heavy-tailed data, often interacting with live, complex systems. However, despite the deepening connections between engineering and modern data science, we argue that training in classical statistical concepts plays a central role in preparing students to solve Google-scale problems. To this end, we present three industrial applications where significant modern data challenges were overcome by statistical thinking.

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