An example of cleaning a data source:
Using http://www.thepocketlab.com/ creates graphs with raw data that usually needs to filtered to make it smoother. Using a Butterworth filter would be an ideal, but this isn't necessary at this level!
Since the data is stored in a .csv it is easily manipulated (and is ideal for this purpose as there are a lot of data points). I like to get students to experiment with changing the frequency of data collected to see how it affects the overal shape of the graph produced. Another activity to try is to get students to predict what the shape should look like and try to manipulate the data to make it look this way. Eventually, we will try methods such as averaging the data for every unit of time (seconds, minutes dependent on data) and discuss how this changes the trendlines.
This makes the experience richer so that the learning is about how data is useful and how graphs are manipulated.
The PocketLab | Wireless sensor for STEM education and makers.
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