It’s too often misused and misunderstood.
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February 16, 2016 · Long read
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When you run an experiment or analyze data, you want to know if your findings are “significant.” But business relevance (i.e., practical significance) isn’t always the same thing as confidence that a result isn’t due purely to chance (i.e., statistical significance). This is an important distinction; unfortunately, statistical significance is often misunderstood and misused in organizations today. And yet because more and more companies are relying on data to make critical business decisions, it’s an essential concept for managers to understand.
Read more on Analytics and data science or related topics Data management and Experimentation
Amy Gallo is a contributing editor at Harvard Business Review, cohost of the Women at Work podcast, and the author of two books: Getting Along: How to Work with Anyone (Even Difficult People) and the HBR Guide to Dealing with Conflict. She writes and speaks about workplace dynamics. Watch her TEDx talk on conflict and follow her on LinkedIn.
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Read more on Analytics and data science or related topics Data management and Experimentation
