What is Statistical Significance?
Statistical significance indicates whether the results of a study are likely to reflect a real effect rather than random chance. It’s a key concept in validating scientific findings.
Key Terms
- P-Value: The probability of seeing results at least as extreme as yours if there were no real effect (that is, if the null hypothesis were true). A p-value below 0.05 is the conventional threshold for calling results statistically significant.
- Confidence Level: Describes how reliable an estimate is: at a 95% confidence level, about 95% of the intervals calculated across many repeated studies would contain the true value.
- Effect Size: Describes the strength or magnitude of the relationship between variables.
Why It Matters
- Helps determine if results are trustworthy.
- Supports or rejects research hypotheses.
- Guides decision-making in scientific studies.
Summary
Statistical significance helps researchers separate meaningful findings from random noise. It ensures that scientific conclusions are backed by evidence, not coincidence.