Statistical significance is a term used to describe the results of a statistical test that are unlikely to have occurred by chance. When a result is statistically significant, it means that there is a strong probability that a real difference exists between the groups being compared.

P value is the probability of obtaining a result at least as extreme as the one observed in the study, assuming that the null hypothesis is true. The null hypothesis is the hypothesis that there is no difference between the groups being compared.

A p value of 0.05 or less is generally considered to be statistically significant. This means that there is a 5% or less chance of obtaining the observed results if the null hypothesis is true.

In the example provided, the p value is 0.034. This means that there is a 3.4% chance of obtaining the observed results if the null hypothesis is true. Since the p value is less than 0.05, we can reject the null hypothesis and conclude that there is a statistically significant difference in memory-test performance between the two groups.

How to Interpret Statistical Significance

It is important to note that statistical significance does not mean that the results of a study are important or meaningful. It simply means that the results are unlikely to have occurred by chance.

For example, a study might find that a new drug is statistically significantly more effective than a placebo at reducing the symptoms of a common cold. However, the difference in effectiveness might be very small, and the new drug might have serious side effects. In this case, the results of the study would be statistically significant, but they would not be important or meaningful.

When interpreting the results of a study, it is important to consider the following factors:

• The p value: A lower p value indicates a stronger probability that the results are real.
• The magnitude of the effect: A larger effect size indicates that the results are more meaningful.
• The clinical significance: Consider whether the results have any practical implications for patients or clinicians.

Conclusion

Statistical significance is an important concept in statistics, but it is important to interpret it correctly. A statistically significant result does not necessarily mean that the results are important or meaningful. It is important to consider the p value, the magnitude of the effect, and the clinical significance when interpreting the results of a study.