Statistically Significant
The likelihood that a result or relationship is caused by something other than mere random chance. Statistical hypothesis testing is traditionally employed to determine if a result is statistically significant or not. This provides a "p-value" representing the probability that random chance could explain the result. In general, a 5% or lower p-value is considered to be statistically significant. Investopedia Says:
This concept may sound confusing and impractical, but consider a simple example - suppose you work for a company that produces running shoes:
You need to plan production for the number of pairs of shoes your company should make in each size for men and for women. You don't want to base your production plans on the anecdotal evidence that men usually have bigger feet than women, you need hard data to base your plans on. Therefore, you should look at a statistical study that shows the correlation between gender and foot size.
If the report's p-value was only 2%, this would be a statistically significant result. You could reasonably use the study's data to prepare your company's production plans, because the 2% p-value indicates there is only a 2% chance that the connection between foot size and gender was the result of chance/error. On the other hand, if the p-value was 20%, it would not be reasonable to use the study as a basis for your production plans, since there would be a 20% chance that the relationship presented in the study could be due to random chance alone. Related Terms:
Correlation
Correlation Coefficient
Covariance
Dispersion
Mutually Exclusive
Regression
Sample Selection Bias |