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chi-squared test中文是什么意思

  • x2检验
  • 卡方检验

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  • 例句与用法
  • Weighted chi - square test
    加权卡方检验
  • Chi - square test
    卡方检验
  • Data was analyzed by frequency distribution , mean , standard deviation , chi - square test , and stepwise regression
    对疾病所抱持的态度,则多呈正向之态度。
  • This calls for a chi - square test of goodness of fit . the percentages need be converted into frequencies for analysis
    这需要用卡方测验来鉴定。并需先将百分数转为频数。
  • The differences between each group of conditions were checked statistically with the chi - square test ( = 0 . 05 )
    对于变频耳声传射异常的学童,随后以纯音听力检查进行追踪。
  • A statistical method , chi - square test , is presented and the actual results arc obtained by experimenting
    并对一种统计攻击方法? ? chi - square深入研究,通过试验数据得出重要结果。
  • The chi - square test result shows that the difference in views between the teachers and students is very unlikely a chance occurrence
    卡方测试的结果显示教师与学生之间见解的差异并非偶然。
  • We used chi - square test , analysis of variance , and logistic regression to determine the factors that affect the choice of delivery mode
    以卡方检定、变异数分析及罗吉斯?归分析,探讨其背景资料之差异与不同族群妇女选用生产方式之影响因素。
  • Sta tis ti cal anal y ses included chi - square test , paired t - test , anal y sis of covariance , one - way anova , and scheffe s post hoc com par i son
    另外,经两组前测为共变项之共变数分析之后,实验组后测之自觉运动利益及运动自我效能分数皆显著高于对照组后测之分数。
  • This paper anglicizes the date by using chi - square test , analysis of variance ( anova ) and liner regression analysis ; brings forth different characteristics of psychological actions and
    最后,本文通过对现象得分析研究其背后产生的原因、掌握其规律,力求能够为博物馆的工作提供现实依据。
  • 更多例句:  1  2
  • 百科解释
A chi-squared test, also referred to as chi-square test or chi^2 test, is any statistical hypothesis test in which the sampling distribution of the test statistic is a chi-squared distribution when the null hypothesis is true, or any in which this is asymptotically true, meaning that the sampling distribution (if the null hypothesis is true) can be made to approximate a chi-squared distribution as closely as desired by making the sample size large enough.
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Last modified time:Sun, 10 Aug 2025 00:29:56 GMT

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