What Is Statistical Significance?

Statistical significance is a determination made by an analyst that the results in data aren't explainable by chance alone. An analyst makes this determination by using statistical 澳洲幸运5官方开奖结果体彩网:hypothesis testing. The test provides a p-value, which is the probabiliওty of observing results as extreme as those in the data assuming 🌳the results are truly due to chance alone.

A p-value of 5% or lower is often considered to be statist🐼ically significant.

Understanding Statistical Significance

Statistical significance is a determination of the 澳洲幸运5官方开奖结果体彩网:null hypothesis, which sugg🐎ests that the results are due to chance alone. A data set provides statistical significance when the p-value is sufficiently small.

The results in the data are explainable by chance alone when the p-value is large and the data are deemed consistent with the null hypothesis (although they don't prove it).

The results aren't easily explained by chance alone when the p-value is sufficiently small, typically 5% or less, and the data are deemed inconsistent with the null hypothesis. In this case, the null hypothesis of chance alone is rejected as an explanation of the data in favor of a more systematic explanation.

Examples of Statistical Significance

Suppose Alex, a financial analyst, is curious as to whether some investors had advance knowledge of a company's sudden failure. Alex decides to compare the average of daily market returns before the company's failure with those after to see if there's a statistically significaꦬnt difference between the two averages.

The study's p-value was 28% (>5%), indicating that a difference as large as the observed (-0.0033 to +0.0007) isn't unusual under the chance-only explanation. The data therefore didn't provide compelling evidence of advance knowledge of the failure.

The observed difference would be very unusual under the chance-only explanation if the p-value was 0.01%, much less than 5%. Alex might decide to reject the null hypothesis in this case aཧnd further investigate whether some traders had advance knowledge.

Statis🅠tical significance is also used to test new medical products including drugs, devices, and vaccines. Publicly available reports of statistical signif💃icance also inform investors about how successful a company is at releasing new products.

Suppose a pharmaceutical leader in diabetes medications reported that there was a statistically significant reduction in diabetes when it tested its new insulin. The test consisted of 26 weeks of randomized therapy among diabetes patients and the data gave a p-value of 4%. This signifies to investors and regulatory agencies that the data show a statistically significant reduction in diabetes.

Stock prices of pharmaceutical companies are often affected by announcements of the statistical significance of their new products.

The Bottom Line

Statistical significance is a result of hypothesis testing that arrives at a p-value or likelihood that two or more variables are caused by something other than chance. A 5% p-value tends to be the dividing line. The lower the value, the more statistically significant the result of the data set is consꦇidered to be.

This form of testing is frequently used to assess pharmaceutical drug trials 💫but it🐼 can be helpful for investors as well, particularly those who want to assess a company that’s releasing a new product.