The new textbook Thinking with Math Models poses an incredibly relevant question to students: is it worthwhile to make math predictions based on data we have gathered even though our predictions are not precise?
Students are so accustomed to finding definitive, 'neat' answers in math that they initially reject the notion that it is possible to simply make reasonable predictions that are not exact.
We started to explore this process with a simple experiment using paper bridges and dimes in a cup. We wanted to know whether the thickness of the bridge (number of stacked layers of papers) would affect the amount of weight our bridges could bear. The data we collected was absolutely not linear (not an exact relationship of papers correlated to bearing weight) but we certainly felt we could draw reasonable conclusions.
As we explore this book further, we will talk about real-world examples of how we make predictions that are often very loosely based on data and yet are incredibly neccessary.
Some examples discussed so far are weather forecasting (anything but exact!), financial planning for retirement and global warming trends.
Home Nugget #3
Assigned on Tuesday October 30 , 2007
Due on Wednesday October 31, 2007
In TWMM (Thinking with Math Models):
Page 18 # 12 - 15 (explain your matches)
Page 19 # 19 - 26 (show your solution process)
From Additional Practice Sheet for Investigation 1:
# 1 - 8 (providing explanations for at least 5 of the problems)
FCAs
2 points: explanations/evidence provided where requested
2 points: you make it very evident that you spent quality time and effort completing the lesson
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