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If we use upper-case letters to indicate results significant at the 0.05 level and lower-case to indicate results significant at the 0.001 level we get: a>b, A’D, a>f, a>g, c>d and c>f. (Often commercial studies use upper-case for significant at the 0.05 level and lower case for significant at the 0.10 level.)
Usually, statistical significance is determined by calculating the probability of error (p value) by the t ratio. The difference between two groups (such as an experiment vs. control group) is judged to be statistically significant when p = 0.05 or less.
Usually, statistical significance is determined by calculating the probability of error (p value) by the t ratio. The difference between two groups (such as an experiment vs. control group) is judged to be statistically significant when p = 0.05 or less.
To find the significance level, subtract the number shown from one. For example, a value of “. 01" means that there is a 99% (1-. 01=.
You may be able to detect a statistically significant difference by increasing your sample size. If you have a very small sample size, only large differences between two groups will be significant. If you have a very large sample size, both small and large differences will be detected as significant.
0:27 2:37 Suggested clip Grafted Prism — Showing significant differences on graphs (v8 YouTubeStart of suggested client of suggested clip Grafted Prism — Showing significant differences on graphs (v8
0:27 2:37 Suggested clip Grafted Prism — Showing significant differences on graphs (v8 YouTubeStart of suggested client of suggested clip Grafted Prism — Showing significant differences on graphs (v8
If your p-value is less than or equal to the set significance level, the data is considered statistically significant. As a general rule, the significance level (or alpha) is commonly set to 0.05, meaning that the probability of observing the differences seen in your data by chance is just 5%.
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