Significant difference
Significant difference
Significant difference (pronunciation: sig-nif-i-cant dif-er-ence) is a term used in statistics to denote a statistical assessment that indicates a difference between two or more sets of data is "real" or significant, and is not due to random chance.
Etymology
The term "significant difference" is derived from the English words "significant" meaning important or noticeable, and "difference" meaning a point or way in which people or things are dissimilar. In the context of statistics, it refers to a difference that is large enough to be of importance or interest.
Definition
In statistical hypothesis testing, a significant difference often refers to the rejection of a null hypothesis. The null hypothesis typically proposes that no significant difference exists; the data sets are the same. If the data suggests otherwise, the null hypothesis is rejected in favor of the alternative hypothesis, which proposes that there is a significant difference.
Related Terms
- P-value: In statistical hypothesis testing, the p-value is the probability of obtaining test results at least as extreme as the results actually observed, under the assumption that the null hypothesis is correct.
- Statistical significance: Statistical significance is the likelihood that the difference in conversion rates between a given variation and the baseline is not due to random chance.
- Confidence interval: A confidence interval is a range of values, derived from a statistical procedure, that is likely to contain the value of an unknown parameter.
- Type I and Type II errors: Type I error occurs when the null hypothesis is true, but is rejected. Type II error occurs when the null hypothesis is false, but is erroneously not rejected.
External links
- Medical encyclopedia article on Significant difference
- Wikipedia's article - Significant difference
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