무선재추출법에 기초한 사건관련전위 자료분석에 대한 탐색적 고찰

An Exploratory Observation of Analyzing Event-Related Potential Data on the Basis of Random-Resampling Method

초록

In hypothesis testing, the interpretation of a statistic obtained from the data analysis relies on a probabilistic distribution of the statistic constructed according to several statistical theories. For instance, the statistical significance of a mean difference between experimental conditions is determined according to a probabilistic distribution of the mean differences (e.g., Student's t) constructed under several theoretical assumptions for population characteristics. The present study explored the logic and advantages of random-resampling approach for analyzing event-related potentials (ERPs) where a hypothesis is tested according to the distribution of empirical statistics that is constructed based on randomly resampled dataset of real measures rather than a theoretical distribution of the statistics. To motivate ERP researchers' understanding of the random-resampling approach, the present study further introduced a specific example of data analyses where a random-permutation procedure was applied according to the random-resampling principle, as well as discussing several cautions ahead of its practical application to ERP data analyses.

키워드

Hypothesis Testing; Random Resampling; Empirical Statistics; ERP Data Analyses; 가설 검증; 무선재추출; 경험적 통계치; ERP 자료 분석
제목
무선재추출법에 기초한 사건관련전위 자료분석에 대한 탐색적 고찰
제목 (타언어)
An Exploratory Observation of Analyzing Event-Related Potential Data on the Basis of Random-Resampling Method
저자
현주석
발행일
2017-06
저널명
감성과학
권
20
호
2
페이지
149 ~ 160