From the course: Data-Driven Decision-Making for the Real World
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How can you empower the business with smart, data-driven decision-making?
From the course: Data-Driven Decision-Making for the Real World
How can you empower the business with smart, data-driven decision-making?
- The biggest issue when working with data is the application of two very valuable terms, correlation and causation. Correlation is simply identifying a relationship, whereas causation is one thing that has a direct effect on another. And this is where you want to be, looking for causation in your data. Take for example, you have sales data that shows there is more foot traffic or people in store on the second Tuesdays of the month. So you have to ask if this simply is a correlation and just happened, or since it was the second Tuesday of the month, it caused people to walk into the store. I'm thinking just a correlation here. But let's consider another example. What if there was an increase in purchases of a particular product in the 30 days following a sales promotion, correlation or causation? This has the potential where one action causes the behavior of another action, and that's where you need to live now with…
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