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That is, the app's impact was statistically significant and provided value. For example, if you've recently implemented a new application to help your office work more efficiently, statistical significance provides you with the confidence in knowing that it made a positive impact on your company's overall workflow. In regards to business, statistical significance is important because it helps you know that the changes you've implemented can be positively attributed to various metrics.

Related: Decision-Making Methods for the Workplace Why is statistical significance important? According to a null hypothesis, there is no relationship between the variables in question. In statistical hypothesis testing, this means the hypothesis is unlikely to have occurred given the null hypothesis. In the use of statistical hypothesis testing, a data set's result can be deemed statistically significant if you have reached a certain level of confidence in the result.

Its two main components are sample size and effect size. In essence, it's a way of proving the reliability of a certain statistic. Statistical significance refers to the likelihood that a relationship between two or more variables is not caused by random chance. Related: Analytical Skills: Definitions and Examples What is statistical significance? In this article, we define statistical significance, its importance and how to calculate it by hand. Though it's known for being taught in statistics coursework, it can be used for a variety of different industries including business. If you're trying to determine the effectiveness of something, consider calculating statistical significance.