简化的卡方检定 减少了卡方
Reduced Chi-Square减少的卡方Chi-Square卡方双语对照例句:1.Or 'I'm sorry, a chi-square test is just too elementary for me to have to explain.' " 或‘对不起,对我来说,卡方检验简直是太基本的常识了,实在是没有必要加以解释.---如有疑问欢迎追问!满意请点击右上方【选为满意回答】按钮反馈 收藏...
Reduced Chi-Square 减少卡方 简化的卡方检定
The reduced chi-squared statistic (Xν2) is used extensively as a goodness of fit test between a model and set of data. It is often referred to as the mean square weighted deviation (MSWD) and is defined by the chi-squared per degree of freedom (Bevington, 1969, Wendt and Carl, 1991...
A 95% confidence interval of the re-excision rate was calculated using the Wilson-Score interval, and the Chi-Square goodness of fit test was used to compare the re-excision rate to the lower end of the currently reported range. The time from initial diagnostic biopsy to completion of ...
Reduced Chi-Sqr 指简化的卡方检验，相当于 anova 里面的 Mean square of Residual，即 rss/dof 残差均方。Chi Square Test是检验三个组的差异是否显著，主要用于间断变量的推断统计,如：已知三组不同性质的人员（老师、家长和学生）对于某一教育举措的观点的不同人数,要对其做总体上三种类型的人对于...
The entry labelled “Chi-Square” is the difference between the two –2 log-likelihood values. Table 4. Results of ordinal regression analysis by respondent group. Group/Test−2 Log LikelihoodChi-SquaredfSig. I: All (pooled sample: n = 145) a) Test of parallel lines Null Hypothesis ...
We propose a unified data-driven reduced order model (ROM) that bridges the performance gap between linear and nonlinear manifold approaches. Deep learning ROM (DL-ROM) using deep-convolutional autoencoders (DC–AE) has been shown to capture nonlinear solution manifolds but fails to perform adequa...
We tested the proportional hazards assumption for the effect of NHS Health Check on the outcome risk using a chi-square test and graphical display of Schoenfeld residuals. In sensitivity analysis, we re-ran the aligned start Cox models with stratified time periods (Therneau and colleagues [24],...
Next, we used the chi-square likelihood ratio test and Akaike’s information criterion (AIC) to test if the model that incorporated the grouping structure actually had a better fit to our data than the model without the grouping structure and included or ignored the grouping structure in all ...