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ISYE 6501 Midterm Quiz 2 with 100% correct answers.
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ISYE 6501 Midterm Quiz 2 with 100% correct answers.
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2021Midterm Quiz 2 - ISYE 6501
90 Minute Time Limit
Instructions
Work alone. Do not collaborate with or copy from anyone else.
Work the problems in any order you wish, but submit each answer
before ending the exam.
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!
https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+1T2021/courseware/f712bb2a96ff46b0bc8d775293bfc91d/
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, 2021
This is 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 change it. There is no overall Submit button.
After submitting all answers, please click the "End my Exam" button, above,
before exiting from ProctorTrack to complete your exam.
Information for Question 1
There are five questions labeled "Question 1." Answer all five
questions. For each of the following five 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 five questions.
These scenarios are meant to be simple and straightforward; if you're
an expert in the field the question asks about, please do not rely on
your expertise to fill in all the extra complexity (you'll end up making
the questions below more difficult than I intended).
Question 1
1.4/1.4 points (graded)
Number of eggs inspected until the first cracked one is found
Geometric
Submit
You have used 1 of 1 attempt
Question 1
1.4/1.4 points (graded)
Number of phone calls made by a telemarketer until one is answered
Geometric
https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+1T2021/courseware/f712bb2a96ff46b0bc8d775293bfc91d/
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, 2021
Submit
You have used 1 of 1 attempt
Question 1
0.0/1.4 points (graded)
Number of arrivals to the ID-check queue at an airport each minute
Exponential
Submit
You have used 1 of 1 attempt
Question 1
0.0/1.4 points (graded)
Number of faces correctly identified by deep learning DL software until
an
error is made
Weibull
Submit
You have used 1 of 1 attempt
Question 1
1.4/1.4 points (graded)
Time between people clicking an online
banner ad
Exponential
Submit
You have used 1 of 1 attempt
https://courses.edx.org/courses/course-v1:GTx+ISYE6501x+1T2021/courseware/f712bb2a96ff46b0bc8d775293bfc91d/
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, 2021
Questions 2a, 2b
5.0/10.0 points (graded)
Five classification 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, filling in the missing data with the average
school rating from the rest of the data.
Model 2 used imputation, building a regression model to fill in the
missing school rating data based on other variables.
Model 3 used imputation, first building a classification 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 classification to select one of
two regression models to fill in an estimate of the school rating;
there are two different regression models (based on other
variables), one for neighborhoods with new schools built due to
population growth, and one for neighborhoods with new schools
built for other reasons.
Model 4 used a binary variable to identify locations with missing
information.
Model 5 used a categorical variable: first, a classification model
was used to estimate whether a new school is likely to have been
built as a result of recent population growth; and then each
neighborhood was categorized as "data available", "missing,
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