with Ed Insel Interpreting Data![]() This week, we started with a warm-up problem and then moved on to interpreting the control charts the students worked on last week. The key message was that by studying data over a long period of time, we can recognize when something undergoes a sudden fundamental shift or begins to slowly drift away from normal. Then we looked over temperature and CO2 charts from as far back as 650 million years. The point was to see how difficult it can be to draw conclusions from even reliable sources of data (NOAA, in this case). But don’t get too focused on climate change – it’s just coincidental that this topic provides good, contemporary examples of the topics we’re covering. Energy, medicine, and space exploration will soon be better sources. ExperimentationOur topic was experimentation, and we used a pendulum as our tool. We learned that we can reduce timing errors by averaging the times across multiple swings. We also learned there are lots of ways energy can be lost from a swinging system. Thermodynamic laws tell us that energy can be neither created nor destroyed but that it can change forms. We experimented with increasing the hanging mass, the height from which we started the pendulum, and the length of the string. From this we learned that the period of oscillation (T) is not a function of mass or drop height – it is only a function of the length of the string. I did not give the class the equation for calculating period but here it is: where l is the length of the pendulum and g is the acceleration due to gravity (9.81 m/s2). Homework for Next SessionThis week’s homework is a reading assignment. Each student has a copy of the Stratfor article “Climate Change: Shifting the Debate to Geopolitics.” The assignment is to read the article and list ten (10) jobs or skill sets that will be needed to address climate change globally. I want you to think broadly about this and not limit yourself to just technologists (examples might be local-language-trained technology implementers, sensor data analysts, solar engineers, agricultural planners, etc.).
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