Indeed, we show that the t statistic explodes asymptotically even under the null, indicating that a mechanical application of the t test yields a serious type I error. To overcome this problem, critical regions
检验的统计量（statistic）也是一个关于样本\textbf{X}的函数，记为\tau(\textbf{X})，那么W=\{\te...
The comparison of the slopes of two regression lines, i.e. the resolution of the null hypothesis test H0:β1=β2⇔β1−β2=0, can be performed by means of a Student’s t-test statistic similar to Eq. (3) and (4). In fact, note that the hypothesis of normality of the ...
To further explore to what extent T cell composition and frequency is distinctive for different B-NHL entities and tumour-free LN, we built classifiers using LASSO-regularized multinomial logistic regression and estimated classification accuracy using nested leave-one-out cross-validation (Fig.3eand Ext...
选择参数检验：检验回归（regression）、比较（comparison）或相关（correlation）三种关系。参数检验通常比非...
Depending on the test you run, you may see other statistics that were used to calculate the P value, including the mean difference, t statistic, degrees of freedom, and standard error. The confidence interval and a review of your dataset is given as well on the results page. ...
问R:基于多元线性回归系数t-统计量计算Cohen's dEN在回归分析中，如果有两个或两个以上的自变量，就称为多元回归。事实上，一种现象常常是与多个因素相联系的，由多个自变量的最优组合共同来预测或估计因变量，比只用一个自变量进行预测或估计更有效，更符合实际。因此多元线性回归比一元线性回归的实用意义更大。
In linear regression, the F-statistic is the test statistic for the analysis of variance (ANOVA) approach to test the significance of the model or the components in the model.
Out[6]: NormaltestResult(statistic=3.292636559115329, pvalue=0.1927582859186863) # 上面的结果统计值是 3.2,p值是0.19,p值0.19是大于0.05的,所以符合 # 此处的normaltest()方法是使用基于偏度和峰度的正态分布检验方法 ss.chi2_contingency([[15, 95], [85, 5]]) ...
In this paper, the robustness of the one-sample t test under non-normal situations is studied. Monte Carlo methods are used to evaluate the significance levels of the test and to analyse the behaviour of the regression curve of the sample variance on the sample mean. In the light of this...