Significant difference

Significant Difference is a term used in statistical analysis to denote the degree of difference between two sets of data that is unlikely to have occurred by chance. The determination of a significant difference is often made through the use of hypothesis testing or confidence intervals.

Overview[edit | edit source]

In statistics, a result is considered significant not because it is important or meaningful, but because it has been predicted as unlikely to have occurred by chance alone. The term "significant" does not imply importance here, but rather that the result is 'statistically significant'.

Statistical Significance[edit | edit source]

Statistical significance is a determination by an analyst that the results in the data are not explainable by chance alone. A study might find that there is a significant difference between two sets of data, but that does not mean the difference is necessarily important, meaningful, or relevant.

Hypothesis Testing[edit | edit source]

In Hypothesis testing, a significant difference often indicates that the null hypothesis can be rejected. The null hypothesis typically proposes that no significant difference exists; it is the hypothesis that the researcher tries to disprove.

Confidence Intervals[edit | edit source]

Confidence intervals are used to estimate the probability that a population parameter will fall between two set values. If the confidence interval does not overlap zero, this suggests a statistically significant difference.

See Also[edit | edit source]

Significant difference Resources
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