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 TestingRandom ResamplingEmpirical StatisticsERP Data Analyses가설 검증무선재추출경험적 통계치ERP 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
20
2
페이지
149 ~ 160