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本文主要通过分析和摘抄几篇文献里对于统计分析结果的表述方法,简单讲解一下SCI论文中的显著性分析结果如何进行描述,以供参考。
1.首先是对于两组数据之间的比较:
两组数据之间进行比较,如下图所示,可以直接标上星号,然后图注里说明。
根据图形类型的不同,可以有不同的描述方法。摘抄文献中的一些句子如下:
the value bars with ns are not significant, asterisk denotes statistically significant differences * p<0.05; **p<0.01; ***p<0.001
* p ≤ 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001 in comparison with DMSO control group
*** indicates significant difference (p<0.001)
Note: symbols on the top of standard error bars indicate the significance of the differences between data for control and SC treatment
* represent significant difference
此外,对于两组数据之间的比较,还可以在图中直接标上P值,如下图所示。
2.对于三组或者更多组数据之间的比较,通常用字母标记法来表示各组之间的差异性。如下图所示。
下面摘抄一些关于三组或者更多组之间关于统计分析描述性的句子,以供参考:
Different low case letters above columns indicate statistical differences at P<0.05
a-bMeans in the same row with different letters differ significantly, P<0.05
groups that do not share the same letter are significantly (P < .05) different from each other
Values with different letters differ significantly (p < 0.05)
Different letters indicate significant differences among groups
values with different uppercase letters are significantly different, P<0.01
Means with the same letter did not significantly differ at P< 0.05, according to Tukey’s test
Different letters indicate significant differences among group at α = 0.05 as determined by Duncan"s multiple range test
Different letters indicate values are significantly different (p < 0.05)
a–cMeans without same superscripts within a column are significantly different (p < 0.01)
Statistical significance is denoted by differing letters (P,0.05)
Columns with the same letters are not significantly different
Different letters meant there was significant difference among groups (p < .05)
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