Question

When testing a new treatment, what is the difference between statistical significance and practical significance? can a treatment have statistical significance, but not practical significance?

Answer 1

Statistical significance is achieved when the outcome is highly unlikely to happen by chance. The practical significance concerns whether conventional treatment makes a difference enough to justify its use. It is possible for a treatment to be statistically significant, but not practical. The correct answer is d.

Given testing new treatments and the difference between statistical and practical significance.

Statistical hypothesis testing is used to determine if the results of a data set are statistically significant. The difference in statistical significance  can be very small.

Statistical significance (reject the null hypothesis) is achieved when the outcome is not likely to occur.

But practical significance means determining whether the difference between samples is significant enough to be of actual significance/meaning simply by common sense.

While statistical significance is concerned with whether or not an effect exists, actual significance is concerned with the magnitude of the effect. However, there is no statistical test that can tell you whether the impact is large enough to matter in your field of study.  Possibly statistically significant but not practical.

Therefore, statistical significance is achieved when the outcome is highly unlikely to happen by chance. Although practical significance is achieved when there is a general perception that the treatments make a large enough difference, the results may be statistically significant but not in practice.

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