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ISYE Midterm Quiz 2 GT Students and Verified MM Learners ISYE6501x Courseware edX.
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4/6/2020 Midterm Quiz 2 - GT Students and Verified MM Learners | Midterm Quiz 2 | ISYE6501x Courseware | edXCourse Midter… Midter… Midter…
Midterm Quiz 2 - GT Students and Veri ed MM Learners
90 Minute Time Limit
Instructions
Work alone. Do not collaborate with or copy from anyone else.
You may use any of the following resources:
One sheet (both sides) of handwritten (not photocopied or scanned) notes
If any question seems ambiguous, use the most reasonable interpretation (i.e. don't be
like Calvin):
Good Luck!
This the beginning of Midterm Quiz 2. Please make sure that you submit all your
answers before the time runs out. Once you submit an answer to a question, you cannot
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,4/6/2020 Midterm Quiz 2 - GT Students and Verified MM Learners | Midterm Quiz 2 | ISYE6501x Courseware | edX
change it. There is no overall Submit button.
Information for Question 1
There are ve questions labeled "Question 1." Answer all ve questions. For each of the
following ve questions, select the probability distribution that could best be used to model
the described scenario. Each distribution might be used, zero, one, or more than one time
in the ve questions.
Question 1
0.0/1.4 points (graded)
Number of people clicking an online banner ad each hour
Exponential
Submit You have used 1 of 1 attempt
Question 1
0.0/1.4 points (graded)
Time between people clicking an online banner ad
Weibull
Submit You have used 1 of 1 attempt
Question 1
0.0/1.4 points (graded)
Time from when a house is put on the market until the rst o er is received
Poisson
Submit You have used 1 of 1 attempt
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, 4/6/2020 Midterm Quiz 2 - GT Students and Verified MM Learners | Midterm Quiz 2 | ISYE6501x Courseware | edX
Question 1
0.0/1.4 points (graded)
Time from the start of a World Cup soccer match until a goal is scored
Poisson
Submit You have used 1 of 1 attempt
Question 1
0.0/1.4 points (graded)
Number of hits to a real estate web site each minute
Binomial
Submit You have used 1 of 1 attempt
Questions 2a, 2b
5.0/10.0 points (graded)
Five classi cation models were built for predicting whether a neighborhood will soon see a
large rise in home prices, based on public elementary school ratings and other factors. The
training data set was missing the school rating variable for every new school (3% of the data
points).
Because ratings are unavailable for newly-opened schools, it is believed that locations that
have recently experienced high population growth are more likely to have missing school
rating data.
Model 1 used imputation, lling in the missing data with the average school rating from
the rest of the data.
Model 2 used imputation, building a regression model to ll in the missing school rating
data based on other variables.
Model 3 used imputation, rst building a classi cation model to estimate (based on
other variables) whether a new school is likely to have been built as a result of recent
population growth (or whether it has been built for another purpose, e.g. to replace a
very old school), and then using that classi cation to select one of two regression
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