{"{0} expected counts are below 5, so the χ² approximation may be poor; Fisher's exact test is better for small tables.":"{0}个期望计数低于5，因此χ²近似可能不理想；对于较小的列联表，Fisher精确检验更合适。","A t-test asks whether a mean differs from a value, or two means from each other, more than chance would explain. Welch's test does not assume equal variances and is the safer default for two groups; the paired test compares two measurements on the same subjects. It assumes roughly normal data or reasonably large samples. A small p-value says the difference is unlikely to be chance, not that it is large or important.":"t检验用于判断一个均值是否与某个值存在超出随机误差所能解释范围的差异，或两个均值之间是否存在这样的差异。Welch检验不假定方差相等，是比较两组数据时更稳妥的默认选择；配对检验比较同一组对象的两次测量结果。它假定数据大致服从正态分布，或样本量足够大。较小的p值表示差异不太可能是由随机误差造成的，但不表示差异一定很大或很重要。","A z-score says how many standard deviations a value lies from the mean: z = (value − mean) ÷ standard deviation. For a normal distribution, the percentile is the share of values below it: z = 1 is the 84th percentile, z = 1.96 the 97.5th, and z = −1 the 16th. Percentiles are only accurate when the data really are close to normal.":"z分数表示某个值距离均值有多少个标准差：z = (值 − 均值) ÷ 标准差。对于正态分布，百分位数表示低于该值的数据所占的比例：z = 1对应第84百分位，z = 1.96对应第97.5百分位，z = −1对应第16百分位。只有当数据确实接近正态分布时，百分位数才是准确的。","Above this value":"高于此值","After (same subjects, same order)":"之后（相同对象，相同顺序）","Alternative":"备择假设","Before (or first measurement)":"之前（或第一次测量）","Below this value":"低于此值","Between groups":"组间","both tails":"双尾","Category":"类别","Chi-square calculator":"卡方计算器","Counts: one row per line, columns separated by spaces":"计数：每行一个，列之间用空格分隔","Cramér's V":"Cramér's V","Degrees of freedom":"自由度","Enter a number.":"请输入一个数字。","Enter a table of at least 2 × 2 counts, with the same number of columns in every row.":"请输入至少为2 × 2的计数表，并确保每行的列数相同。","Enter a value, a mean, and a standard deviation above zero.":"请输入一个值、一个均值，以及一个大于0的标准差。","Enter at least two counts of zero or more.":"请输入至少两个大于或等于0的计数。","Enter at least two groups, each with at least two values, one group per line.":"请输入至少两组数据，每组至少包含两个值，每行一组。","Enter at least two values in each group.":"请输入每组至少两个值。","Enter the value to compare with.":"请输入用于比较的值。","Expected":"期望","Expected counts if rows and columns were independent":"行与列相互独立时的期望计数","Expected proportions (optional; equal if empty)":"期望比例（可选；留空则视为相等）","Further from the mean":"距离均值更远","Give one expected proportion above zero for each count, or leave it empty.":"为每个计数输入一个大于0的期望比例，或留空。","Goodness of fit":"拟合优度","Greater (>)":"大于（>）","Group":"组","Group A values":"组A值","Group B values":"组B值","Independence (table)":"独立性（列联表）","Less (<)":"小于（<）","Mean":"均值","Mean difference":"均值差","Means":"均值","Normal curve with the area below z shaded":"标出z以下区域的正态曲线","Not significant at the 5% level (p ≥ 0.05): the data are consistent with no real difference.":"在5%显著性水平上不显著（p ≥ 0.05）：数据与不存在实际差异的情况一致。","Observed":"观测","Observed counts":"观测计数","One group per line, values separated by spaces or commas":"每行一组，值之间用空格或逗号分隔","One sample":"单样本","One-way analysis of variance tests whether several group means are all equal, by comparing the variation between groups with the variation within them: F = MS between ÷ MS within. A small p-value says at least one mean differs, not which; follow up with pairwise tests and a correction such as Tukey's or Bonferroni's. It assumes independent observations, roughly normal data, and similar variances.":"单因素方差分析通过比较组间变异与组内变异，检验多个组的均值是否全部相等：F = 组间MS ÷ 组内MS。较小的p值表示至少有一个均值不同，但不能说明是哪一个；请进一步进行两两检验，并使用Tukey或Bonferroni等校正方法。该检验假定观测值相互独立、数据大致服从正态分布，且方差相近。","One-way ANOVA calculator":"单因素ANOVA计算器","p-value":"p值","Paired samples":"配对样本","Paired samples need the same number of values in both lists ({0} and {1}).":"配对样本的两个列表必须包含相同数量的值（{0}和{1}）。","percentile":"百分位数","Percentile (%)":"百分位数（%）","Percentile to z":"百分位数转z","Sample mean":"样本均值","Sample values":"样本值","SD {0} and {1}":"SD {0}和{1}","SD {0}, n = {1}":"SD {0}，n = {1}","share of variance between groups":"组间方差占比","Significant at the 5% level (p < 0.05): the result would be unlikely if there were no real difference.":"在5%显著性水平上显著（p < 0.05）：如果不存在实际差异，这一结果不太可能出现。","Source":"变异来源","Standard deviation":"标准差","strength of association, 0 to 1":"关联强度，0到1","T-test calculator":"t检验计算器","Test":"检验","The χ² test compares observed counts with the counts expected if there were no effect: χ² = Σ (observed − expected)² ÷ expected. The test of independence asks whether two categorical variables are related, from a table of counts; goodness of fit asks whether counts follow given proportions. Use raw counts, not percentages, and no continuity correction is applied.":"χ²检验将观测计数与不存在效应时的期望计数进行比较：χ² = Σ (观测 − 期望)² ÷ 期望。独立性检验根据计数表判断两个分类变量是否相关；拟合优度检验判断计数是否符合给定比例。请使用原始计数，而不是百分比；系统不会进行连续性校正。","Two samples (equal variances)":"双样本（方差相等）","Two samples (Welch)":"双样本（Welch）","Two-sided (≠)":"双侧（≠）","Value":"值","Value to compare with (μ₀)":"用于比较的值（μ₀）","Value to z":"值转z","Within groups":"组内","Work out":"计算","Z to percentile":"Z转百分位数","Z-score":"Z分数","Z-score calculator":"Z分数计算器"}