方差与协方差分析
方差分析 (ANOVA) 是指将样本方差指定给不同的源,然后确定变异产生于不同总体组内还是组间的过程。样本用组均值的变异和总体均值的变异来描述。如果组内的变异相对于组间的变异较小,则可以推断出组均值的差异。假设检验用于量化决策。Statistics and Machine Learning Toolbox™ 提供几种执行 ANOVA 的方式,包括 anova
对象、命令行函数和交互式 App。
函数
主题
- One-Way ANOVA
Use one-way ANOVA to determine whether data from several groups (levels) of a single factor have a common mean.
- 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.