5/1/2020 Midterm Quiz 2 - GT Students and Verified M
GTx: ISYE6501x
Introduction to Analytics Modeling
Midterm Quiz 2 - GT Students and
Course Midterm Quiz 2 - Spring 2020 Midterm Quiz 2 Veri ed MM Learners
Midterm Quiz 2 - GT Students and Veri ed MM
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)
If any question seems ambiguous, use the most reasonable interpretat
Good Luck!
This the beginning of Midterm Quiz 2. Please make sure that you subm
answer to a question, you cannot change it. There is no overall Submit
Information for Question 1
There are ve questions labeled "Question 1." Answer all ve questions.
distribution that could best be used to model the described scenario. Ea
, 5/1/2020 Midterm Quiz 2 - GT Students and Verified M
1.4/1.4 points (graded)
Time from when a generator is turned on until it fails
Weibull
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 neighborho
school ratings and other factors. The training data set was missing the sc
Because ratings are unavailable for newly-opened schools, it is believed t
more likely to have missing school rating data.
Model 1 used imputation, lling in the missing data with the average
Model 2 used imputation, building a regression model to ll in the mi
Model 3 used imputation, rst building a classi cation model to estim
been built as a result of recent population growth (or whether it has b
then using that classi cation to select one of two regression models t
regression models (based on other variables), one for neighborhoods
neighborhoods with new schools built for other reasons.
Model 4 used a binary variable to identify locations with missing infor
Model 5 used a categorical variable: rst, a classi cation model was u
result of recent population growth; and then each neighborhood was
"missing, other reason".
a. If school ratings cannot be reasonably well-predicted from the other fa
reasonably well-classi ed using the other factors, which model would you
Model 1
Model 2
Model 3
Model 4
Model 5
GTx: ISYE6501x
Introduction to Analytics Modeling
Midterm Quiz 2 - GT Students and
Course Midterm Quiz 2 - Spring 2020 Midterm Quiz 2 Veri ed MM Learners
Midterm Quiz 2 - GT Students and Veri ed MM
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)
If any question seems ambiguous, use the most reasonable interpretat
Good Luck!
This the beginning of Midterm Quiz 2. Please make sure that you subm
answer to a question, you cannot change it. There is no overall Submit
Information for Question 1
There are ve questions labeled "Question 1." Answer all ve questions.
distribution that could best be used to model the described scenario. Ea
, 5/1/2020 Midterm Quiz 2 - GT Students and Verified M
1.4/1.4 points (graded)
Time from when a generator is turned on until it fails
Weibull
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 neighborho
school ratings and other factors. The training data set was missing the sc
Because ratings are unavailable for newly-opened schools, it is believed t
more likely to have missing school rating data.
Model 1 used imputation, lling in the missing data with the average
Model 2 used imputation, building a regression model to ll in the mi
Model 3 used imputation, rst building a classi cation model to estim
been built as a result of recent population growth (or whether it has b
then using that classi cation to select one of two regression models t
regression models (based on other variables), one for neighborhoods
neighborhoods with new schools built for other reasons.
Model 4 used a binary variable to identify locations with missing infor
Model 5 used a categorical variable: rst, a classi cation model was u
result of recent population growth; and then each neighborhood was
"missing, other reason".
a. If school ratings cannot be reasonably well-predicted from the other fa
reasonably well-classi ed using the other factors, which model would you
Model 1
Model 2
Model 3
Model 4
Model 5
