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GTx: ISYE6501x Introduction to Analytics Modeling Midterm Quiz 2( Complete Solution)
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GTx: ISYE6501x Introduction to Analytics Modeling Midterm Quiz 2( Complete Solution)
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5/1/2020 Midterm Quiz 2 - GT Students and Verified MGTx: 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
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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
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Time from when a generator is turned on until it fails
Weibull
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Questions 2a, 2b
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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
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