Sampling Statistical Errors in Big Data Research: 3 Cases of Breast Cancer Research

Abstract

AbstractBreast cancer is a major cause of female death, and various big data analysis methods have been applied to breast cancer. This study lists cases in which big data analysis was applied to breast cancer research. In addition, statistics and percentages from each specific sample were proposed. However, research on the use of big data has a blind spot that relies on sample characteristics. Therefore, before sampling big data, statistical inference should be discussed more precisely through pre-examination and sample statistical errors should be reduced by professional statistical evaluation of the analysis method. In particular, the control and experimental groups should be statistically equivalent.