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분산분석과 공분산 분석
함수
anova1 | 일원분산분석 |
anova2 | 이원분산분석 |
anovan | 다원분산분석 |
aoctool | Interactive analysis of covariance |
canoncorr | Canonical correlation |
dummyvar | Create dummy variables |
friedman | Friedman’s test |
kruskalwallis | Kruskal-Wallis test |
multcompare | 다중 비교 검정 |
예제 및 방법
- 일원분산분석(One-way ANOVA)
일원분산분석을 사용하여 단일 인자의 여러 그룹(수준)에 있는 데이터가 공통 평균을 갖는지 확인합니다.
- Two-Way ANOVA
In two-way ANOVA, the effects of two factors on a response variable are of interest.
- N-Way ANOVA
In N-way ANOVA, the effects of N factors on a response variable are of interest.
- ANOVA with Random Effects
ANOVA with random effects is used where a factor's levels represent a random selection from a larger (infinite) set of possible levels.
- Other ANOVA Models
N-way ANOVA can also be used when factors are nested, or when some factors are to be treated as continuous variables.
- Multiple Comparisons
Multiple comparison procedures can accurately determine the significance of differences between multiple group means.
- Analysis of Covariance
Analysis of covariance is a technique for analyzing grouped data having a response (y, the variable to be predicted) and a predictor (x, the variable used to do the prediction).
- Nonparametric Methods
Statistics and Machine Learning Toolbox™ functions include nonparametric versions of one-way and two-way analysis of variance.
개념
- Introduction to Analysis of Variance
Analysis of variance (ANOVA) is a procedure for assigning sample variance to different sources and deciding whether the variation arises within or among different population groups.