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ISYE 6501 Final EXAM ALL QUESTIONS AND
CORRECT ANSWERS LATEST UPDATE THIR
YEAR
QUESTION: Select the type of problem that GARCH is best suited for.
- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data
- Prediction from feature data
- Variable selection - ANSWER-- Prediction from Time-series data
Useful when you want to model and forecast the volatility of financial time series data (e.g.,
stock returns) and have data with time-varying variance.
QUESTION: Select the type of problem that exponential smoothing is best suited for.
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, Page 2 of 50
- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data
- Prediction from feature data
- Variable selection - ANSWER-- Prediction from time-series data
Useful when you want to generate short-term forecasts based on weighted averages of past
observations and have time series data with trends or seasonality.
QUESTION: Select the type of analysis that ARIMA is best suited for.
- Using feature data to predict the amount of something two time periods in the future
- Using feature data to predict the probability of something happening two time periods in the
future
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, Page 3 of 50
- Using feature data to predict whether or not something will happen two time periods in the
future
- Using time-series data to predict the amount of something two time periods in the future
- Using time-series data to predict the variance of something two time periods in the future -
ANSWER-Using time-series data to predict the amount of something two time periods in the
future
Remeber, ARIMA is useful when you want to forecast future values in a time series (e.g., stock
prices, sales) and have historical time-ordered data available.
QUESTION: Select the type of analysis that a random linear regression forrest is best suited for.
- Using feature data to predict the amount of something two time periods in the future
- Using feature data to predict the probability of something happening two time periods in the
future
- Using feature data to predict whether or not something will happen two time periods in the
future
- Using time-series data to predict the amount of something two time periods in the future
3
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- Using time-series data to predict the variance of something two time periods in the future -
ANSWER-Using feature data to predict the amount of something two time periods in the future
QUESTION: Select the type of analysis that a support vector machine is best suited for.
- Using feature data to predict the amount of something two time periods in the future
- Using feature data to predict the probability of something happening two time periods in the
future
- Using feature data to predict whether or not something will happen two time periods in the
future
- Using time-series data to predict the amount of something two time periods in the future
- Using time-series data to predict the variance of something two time periods in the future -
ANSWER-Using feature data to predict whether or not something will happen two time periods
in the future
QUESTION: Select the type of analysis that a k-nearest-neighbor classification tree is best suited
for.
4
ISYE 6501 Final EXAM ALL QUESTIONS AND
CORRECT ANSWERS LATEST UPDATE THIR
YEAR
QUESTION: Select the type of problem that GARCH is best suited for.
- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data
- Prediction from feature data
- Variable selection - ANSWER-- Prediction from Time-series data
Useful when you want to model and forecast the volatility of financial time series data (e.g.,
stock returns) and have data with time-varying variance.
QUESTION: Select the type of problem that exponential smoothing is best suited for.
1
, Page 2 of 50
- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data
- Prediction from feature data
- Variable selection - ANSWER-- Prediction from time-series data
Useful when you want to generate short-term forecasts based on weighted averages of past
observations and have time series data with trends or seasonality.
QUESTION: Select the type of analysis that ARIMA is best suited for.
- Using feature data to predict the amount of something two time periods in the future
- Using feature data to predict the probability of something happening two time periods in the
future
2
, Page 3 of 50
- Using feature data to predict whether or not something will happen two time periods in the
future
- Using time-series data to predict the amount of something two time periods in the future
- Using time-series data to predict the variance of something two time periods in the future -
ANSWER-Using time-series data to predict the amount of something two time periods in the
future
Remeber, ARIMA is useful when you want to forecast future values in a time series (e.g., stock
prices, sales) and have historical time-ordered data available.
QUESTION: Select the type of analysis that a random linear regression forrest is best suited for.
- Using feature data to predict the amount of something two time periods in the future
- Using feature data to predict the probability of something happening two time periods in the
future
- Using feature data to predict whether or not something will happen two time periods in the
future
- Using time-series data to predict the amount of something two time periods in the future
3
, Page 4 of 50
- Using time-series data to predict the variance of something two time periods in the future -
ANSWER-Using feature data to predict the amount of something two time periods in the future
QUESTION: Select the type of analysis that a support vector machine is best suited for.
- Using feature data to predict the amount of something two time periods in the future
- Using feature data to predict the probability of something happening two time periods in the
future
- Using feature data to predict whether or not something will happen two time periods in the
future
- Using time-series data to predict the amount of something two time periods in the future
- Using time-series data to predict the variance of something two time periods in the future -
ANSWER-Using feature data to predict whether or not something will happen two time periods
in the future
QUESTION: Select the type of analysis that a k-nearest-neighbor classification tree is best suited
for.
4
