## What does 'Statistically Significant' mean

Statistically significant is the likelihood that a relationship between two or more variables is caused by something other than random chance. Statistical hypothesis testing is used to determine whether the result of a data set is statistically significant. This test provides a p-value, representing the probability that random chance could explain the result; in general, a p-value of 5% or lower is considered to be statistically significant.

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## BREAKING DOWN 'Statistically Significant'

Specifically, a set of data becomes statistically significant when the set is large enough to accurately represent the phenomenon or population sample being studied. A data set is deemed to be statistically significant if the probability of the phenomenon being random is less than one out of every 20, which is why the p-value is set at 5%.

## Statistically Significant Data in Theory

Suppose a person works for a company that produces running shoes. He needs to plan production for the number of shoes that his company should make in each size, for both men and for women. He doesn't want to base his production plans on the anecdotal evidence that men usually have bigger feet than women. He needs hard data to devise an accurate forecast. Therefore, he should look at a statistical study that shows the correlation between gender and foot size.

If the study's p-value was 2%, it would have a statistically significant result. He could then reasonably use the study's data to prepare his company's production plans, because the p-value indicates there is only a 2% chance that the connection between foot size and gender was the result of chance. On the other hand, if the p-value was 6%, it would not be reasonable to use the study as a basis for his production plans. So, if the study with the 2% p-value said that most men were found to have a shoe size between eight and 12, and women were found to have a shoe size between four and eight, he could confidently produce a majority of shoes in each one of those sizes, for each gender.

## Statistically Significant Data in Practice

Often times, the idea of statistical significance is used in new drug trials for pharmaceutical companies. This is important for two reasons: The first is that the drug itself is tested for effectiveness, and the second is that it tells investors how successful the company is at releasing new products.

For example, Novo Nordisk, the pharmaceutical leader in diabetes medication, reported on June 2016, that there was a statistically significant reduction in type 1 diabetes when it tested its new insulin. The test consisted of 26 weeks of randomized therapy among diabetes patients, reduced type 1 diabetes and had a p-value of less than 5%, meaning that the reduction in diabetes was not due to random chance.

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