μ:总体均值(Population Mean)σ:总体标准差(Population Standard Deviation)X̄:样本均值(Sample Mean)s:样本标准差(Sample Standard Deviation)N:总体大小(Population Size)n:样本大小(Sample Size)Σ:求和符号(Summation)∑:累计符号(Cumulative Sum)α:显著性水平(Significance Level)β:第二类错误概率(Type II Error Probability)p:概率(Probability)H₀:零假设(Null Hypothesis)H₁:备择假设(Alternative Hypothesis)CI:置信区间(Confidence Interval)t:t值(t-value)F:F值(F-value)χ²:卡方值(Chi-Square Value)R:相关系数(Correlation Coefficient)r:相关系数(Correlation Coefficient)p-value:显著性水平(p-value)
PART 2
SD:标准差(Standard Deviation)SE:标准误(Standard Error)df:自由度(Degrees of Freedom)CI:置信区间(Confidence Interval)p值:显著性水平(p-value)p<0.05:显著性水平小于0.05ANOVA:方差分析(Analysis of Variance)t检验:独立样本t检验(t-test)dF:自由度(Degrees of Freedom)Pearson相关系数:皮尔逊相关系数ICC:一致性相关系数(Intraclass Correlation Coefficient)SEM:结构方程模型(Structural Equation Modeling)C.I.: 置信区间(Confidence Interval)C.V.: 变异系数(Coefficient of Variation)IQR:四分位数间距(Interquartile Range)OR:比值比(Odds Ratio)C.R:临界比率(Critical Ratio)
PART 3
OLS:最小二乘法(Ordinary Least Squares)PLS:偏最小二乘回归(Partial Least Squares Regression)LDA:线性判别分析(Linear Discriminant Analysis)SSR:回归平方和(Sum of Squares Regression)SSE:残差平方和(Sum of Squares Error)SST:总平方和(Total Sum of Squares)BIC:贝叶斯信息准则(Bayesian Information Criterion)VIF:方差膨胀因子(Variance Inflation Factor)MSE:均方误差(Mean Squared Error)RMSE:均方根误差(Root Mean Squared Error)R²:决定系数(Coefficient of Determination)GLM:广义线性模型(Generalized Linear Model)RMSE:均方根误差(Root Mean Square Error)ROC曲线:受试者工作特征曲线(Receiver Operating Characteristic Curve)GEE:广义估计方程(Generalized Estimating Equations)MLR:多元线性回归(Multiple Linear Regression)