From the course: The Data Science of Experimental Design
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Data handling
- [Instructor] Before we go too far, I want to talk about data collection and handling. Earlier I showed you some Excel spreadsheets with data and time series graphs. That might have made the project look a little too easy. In real life, putting together the data on those spreadsheets was not an obvious task. It is true that dashboards like the ones offered by Google Analytics and Twitter Analytics provide you with data, and you can set filters, save reports, and even export data. Even though you have that flexibility, you have to know what you are doing and what exact data you need. Let's say you designed some rates and now you want to graph them. You know how you will count them. You put that on your planning sheet. But literally, what filters do you set? Or what reports do you look at? Or what data do you export to get the aggregated numerators and denominators you need by the time period you selected? Remember…
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