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  • Results should not be reported as statistically significant or . . .
    When results are not „statistically significant‟ it cannot be assumed that there was no impact Typically a cut-off of 5% is used to indicate statistical significance This means that the results are considered to be „statistically non-significant‟ if the analysis shows that differences as
  • 数据分析中常被混淆的术语 - 知乎
    在科学性的写作中，"significant" 这个词一般与 "statistically significant" 同义。 "Nonsignificant" 有着相反的含义，也就是 "not statistically significant"。 相比而言，"insignificant" 通常意味着 非统计学 上的意义上的“不重要”。
  • My results were not significant… now what? - Statistics Solutions
    You didn’t get significant results Now you may be asking yourself, “What do I do now?” “What went wrong?” “How do I fix my study?” One of the most common concerns that I see from students is about what to do when they find non-significant results
  • How do you discuss results which are not statistically significant in a . . .
    A result may possibly be due to chance, eg at p=6%, yet it may still be the most likely of the alternative explanations, or consistent with a previous statistically significant result so
  • 统俗讲义之——何为统计显著性(Statistical Significance . . .
    其中Alpha，就是当“零假设”是对的，你却拒绝了它，的概率，我们称它为“显著水平”(Significance Level)。 比如若将Alpha设定为0 05，那么就是允许你的检验有5%的概率拒绝接受一个已知的正确的结论。
  • Interpreting a not statistically significant result. Five possible . . .
    You find that the P value is large enough for you to conclude that the result is not statistically significant Below are five explanations to explain why this happened Explanation 1: The drug didn't work The drug did not induce or activate the enzyme you are studying, so the enzyme’s activity is the same (on average) in treated and control
  • The earnestness of being important: Reporting non‐significant . . .
    A more appropriate way to report non-significant results is to report the observed differences (the effect size) along with the p-value and then carefully highlight which results were predicted to be different This considered approach avoids issues with con-fusing effect size with significance as providing a p-value with-
  • Improving the utility of non-significant results for educational . . .
    Within a random sample of 50 peer-reviewed articles, we found that of 528 statistically tested hypotheses, 253 (48%) were non-significant Of these, 142 (56%) were erroneously interpreted to indicate the absence of an effect, and 59 (23%) to indicate a difference to another significant effect
  • The difference between “significant” and “not significant” is not . . .
    It is common to summarize statistical comparisons by declarations of statistical significance or non-significance Here we discuss one problem with such declarations, namely that changes in statistical significance are often not themselves statistically significant
  • Publishing Findings that are Not Significant: Can Non-significant . . .
    The research study was in science education and the results were not statistically significant During the committee deliberations after the student was excused, the physicist raised the question of whether results that were not significant could result in a decision to pass the student





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