1. Reading. Read Chapter 1-3 of Tufte. Read Chapter 3 of BFFG (https://m3challenge.siam.org/

sites/default/files/uploads/siam-technical-guidebook-web.

pdf). 2. On p. 11 of BFG, they present the following focal problem: “Create

a mathematical model that ranks roller coasters according to a thrill

factor that you define.”

Determine dependent and independent variables for ranking roller

coasters based on how thrilling they are. What are some possible

model parameters?

Remark: To do this problem successfully, you’ll also need to do some

earlier steps (such as brainstorming, perhaps through a mind map). It

is also required to submit these items as part of your problem solution. 3. Continue working with your model for a ranking system for roller

coasters using your definition of “hrilling.” Use your ranking system to

rank at least 10 roller coasters. (You can find data to use at rcdb.com.)

Remark: Depending on the formulation of your model, it may be

necessary for this problem to simplify it to obtain something that you

know how to solve mathematically. That’s fine but indicate explicitly

in this problem what additional assumptions you make in order to

simplify the problem, and comment on any possible new limitations

or errors that may arise from this process. 4. Find a data visualization from 2020 (e.g., from an online “newspaper” or “magazine”) that you really like. Indicate why you like

it, and also enumerate both its strengths and its weaknesses. Find a data visualization from 2020 (e.g., from an online “newspaper” or “magazine”) that has a “lie factor” or something else

that makes it misleading. Enumerate both the strengths and the

weaknesses of this visualization. Using the second visualization above, sketch the design of a better

visualization that shows the data in a less misleading manner. (If

the example you found above is totally irredeemable, feel free to

do this part of the question with a different graphic.) 5. Find some data set somewhere and create your own visualization with

that data set.

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