'What Is The Significance Of Time-Weighted Averages In Data Analysis' by HarlemCavalier datascience sql
What are time-weighted averages?
When we’d do R&D for new battery formulations, we’d cycle many batteries many times to figure out which formulations make batteries last the longest. It let us answer more interesting questions about the quickly changing parts of the curve and gave us all the information we needed about the slowly changing sections – without storing gobs of redundant data.That question is important because it was one of the things we could compare between this discharge curve and future ones, say 10 or 100 cycles later.
We could easily overlook any of the differences we were trying to identify – and any clues about how we could improve the batteries could just get lost in the variation of our sampling protocol. One cool thing to note is that this gives us a new way to think about this solution: it’s the average of each pair of adjacent values, weighted by the time between them:It’s also equal to the area of the rectangle drawn to the midpoint between v1 and v2:
Let’s consider the scenario of an ice cream manufacturer or shop owner who is monitoring their freezers. It turns out that ice cream needs to stay in a relatively narrow range of temperatures so that it doesn’t melt and re-freeze, causing those weird crystals that no one likes. Similarly, if ice cream gets too cold, it’s too hard to scoop.
The period after the door opens, minutes 31-36, has a lot more data points. If we were to take the average of all the points, we would get a misleading value. The freezer was only above the threshold temperature for 5 out of 45 minutes , but those minutes make up 10 out of 20 data points because we sample freezer temperature more frequently after the door is opened.
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