A result that is significant at the 1% level means that there is a 1% chance of observing the obtained results if there were no real effect or relationship between the variables being studied.
In simpler terms, it means that the findings are unlikely to have occurred by chance.
Here's a breakdown of what this signifies:
- Statistical Significance: The term "significant" in statistics refers to the likelihood of observing a particular result if there were no real effect or relationship between the variables.
- P-value: The p-value is a probability that represents the likelihood of observing the obtained results or more extreme results if there were no real effect.
- 1% Significance Level: A 1% significance level means that the p-value is less than 0.01. This indicates that there is a 1% chance of observing the obtained results if there were no real effect.
- Confidence: A 1% significance level provides a high level of confidence that the observed results are not due to chance.
Example:
Let's say a researcher is studying the effectiveness of a new drug. They conduct a study and find that the drug is effective in reducing symptoms. The p-value for this result is 0.005, which is less than 0.01. This means that there is a 0.5% chance of observing the obtained results if the drug had no real effect. Therefore, the researcher can conclude that the drug is effective at the 1% significance level.
Practical Implications:
- Strong Evidence: A 1% significance level provides strong evidence to support the research hypothesis.
- Reduced Risk of Type I Error: A lower significance level reduces the risk of a Type I error, which occurs when a researcher rejects the null hypothesis when it is actually true.
- Decision Making: Researchers often use significance levels to make decisions about whether to accept or reject a hypothesis.
Conclusion:
A result that is significant at the 1% level provides strong evidence to support the research hypothesis. It indicates that the observed results are unlikely to have occurred by chance, and there is a high level of confidence that the findings are real.
