Analysis Of Statistical Data on Dementia and Seeking Potential Correlations and Research Directions

Chenlai Zheng

doi:10.54097/hset.v45i.7367

Authors

Chenlai Zheng

DOI:

https://doi.org/10.54097/hset.v45i.7367

Keywords:

Dementia; Alzheimer's disease; statistics; data analysis; R language.

Abstract

Modern human society is plagued by many diseases that were previously unappreciated, dementia being one of these diseases. Due to advances in modern medicine, the average human lifespan has increased greatly. However, many diseases have also emerged as a result of the longevity of humans. This article tries to find the potential factors that lead to dementia by analyzing data from a dementia study of 150 subjects at Washington University. The paper focuses on screening and analyzing the data by using R language and programs, and the proportions of subjects were calculated and compared according to gender. In addition, age, eTIV, nWBV, and ASF were subjected to binary analysis and scatterplots in permutations and combinations. The study did not find potential associations for variables other than eTIV and ASF. This study primarily used data statistics and analysis to provide possible potential research directions for clinical researchers in this field, with the hope that future research will lead to breakthroughs in Alzheimer's disease (AD).

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