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Q
uantitative
R
easoning &
P
roblem
S
olving
144
© 2014 Pacific Crest
8. Why can we justify modeling data as continuous when our collection of data is inherently going to
be discrete?
A
Successful Performance
Successful application of your learning looks like this
As you begin to apply what you’ve learned, you should have a good idea of what success looks like.
A SUCCESSFUL
PERFORMANCE
I use probability distributions to analyze and explain patterns of randomness. I
●
Explore the context of a random phenomena and evaluate its data
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Analyze data through the construction of a distribution
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Determine which distribution matches the data
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Validate that the distribution fits the phenomen
a
D
emonstrate Your Understanding
Apply it and show you know in context!
1. Suppose you randomly guess on a multiple choice test. Create a probability distribution for the
possible grades. What is the likelihood that you pass? What other situations follow this same
distribution?
2. Create a probability distribution for file sizes of internet traffic with TCP protocol. How is this
information useful for ISPs? What other situations follow this same distribution?
3. Create a probability distribution for the times when tickets are bought before a performance such as
a concert. How can this be used to establish a pricing schedule for when to raise the cost of tickets
as the time of the event approaches? What other situations follow this same distribution?.
H
ardest Problem
How hard
can
it be? Can you still use what you’ve learned?
Based on the Model, the Methodology, and the Demonstrate Your Understanding (DYU) problem in
this activity, create the
hardest
problem you can. Start with the hardest DYU problem in this experience
and by contrasting and comparing it with the other DYU problems, play “What if” with the different
conditions and parameters in the various problems.
Can you still solve the problem? If so, solve it. If not, explain why not. What is it that makes a problem
involving probability distribution a difficult problem to solve?
What are the conditions and parameters that make a problem involving probability distribution a difficult
problem to solve?