ISYE 6501 Final Exam | Georgia Tech | 2025/2026
Edition | Verified Exam Questions with Answers
1-norm - ...ANSWER✓✓✓Similar to rectilinear distance;
measures the straight-line length of a vector from the origin. If
z=(z1,z2,...,zm) is a vector in an m-dimensional space, then it's 1-
norm is square root(|𝑧1|+|𝑧2|+⋯+|𝑧𝑚| = |𝑧1|+|𝑧2|+⋯+|𝑧| = Σm over
i=1 |𝑧𝑖|
2-norm - ...ANSWER✓✓✓Similar to Euclidian distance; measures
the straight-line length of a vector from the origin. If
z=(z1,z2,...,zm) is a vector in an 𝑚-dimensional space, then its 2-
norm is the same as 1-norm but everything is squared= square
root(Σm over i=1 (|𝑧𝑖|)^2)
A/B Testing - ...ANSWER✓✓✓testing two alternatives to see
which one performs better
Accuracy - ...ANSWER✓✓✓Fraction of data points correctly
classified by a model; equal to TP+TN / TP+FP+TN+FN
Action - ...ANSWER✓✓✓In ARENA, something that is done to an
entity.
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Additive Seasonality - ...ANSWER✓✓✓Seasonal effect that is
added to a baseline value (for example, "the temperature in June
is 10 degrees above the annual baseline").
Adjusted R-squared - ...ANSWER✓✓✓Variant of R2 that
encourages simpler models by penalizing the use of too many
variables.
AIC - ...ANSWER✓✓✓Akaike information criterion- Model
selection technique that trades off between model fit and model
complexity. When comparing models, the model with lower AIC is
preferred. Generally penalizes complexity less than BIC.
Algorithm - ...ANSWER✓✓✓Step-by-step procedure designed to
carry out a task.
Analysis of Variance/ANOVA - ...ANSWER✓✓✓Statistical method
for dividing the variation in observations among different
sources.
Approximate dynamic program - ...ANSWER✓✓✓Dynamic
programming model where the value functions are
approximated.
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Arc - ...ANSWER✓✓✓Connection between two nodes/vertices in
a network. In a network model, there is a variable for each arc,
equal to the amount of flow on the arc, and (optionally) a capacity
constraint on the arc's flow. Also called an edge.
Area under the curve (AUC) - ...ANSWER✓✓✓Area under the
ROC curve; an estimate of the classification model's accuracy.
Also called concordance index.
ARIMA - ...ANSWER✓✓✓Autoregressive integrated moving
average.
Arrival Rate - ...ANSWER✓✓✓Expected number of arrivals of
people, things, etc. per unit time -- for example, the expected
number of truck deliveries per hour to a warehouse.
Assignment Problem - ...ANSWER✓✓✓Network optimization
model with two sets of nodes, that finds the best way to assign
each node in one set to each node in the other set.
Attribute - ...ANSWER✓✓✓A characteristic or measurement - for
example, a person's height or the color of a car. Generally
interchangeable with "feature", and often with "covariate" or
"predictor". In the standard tabular format, a column of data.
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Autoregression - ...ANSWER✓✓✓Regression technique using
past values of time series data as predictors of future values.
Autoregressive integrated moving average (ARIMA) -
...ANSWER✓✓✓Time series model that uses differences between
observations when data is nonstationary. Also called Box-
Jenkins.
Backward elimination - ...ANSWER✓✓✓Variable selection
process that starts with all variables and then iteratively
removes the least-immediately-relevant variables from the
model.
Balanced Design - ...ANSWER✓✓✓Set of combinations of factor
values across multiple factors, that has the same number of
runs for all combinations of levels of one or more factors.
Balking - ...ANSWER✓✓✓An entity arrives to the queue, sees the
size of the line (or some other attribute), and decides to leave the
system.
Bayes' theorem/Bayes' rule - ...ANSWER✓✓✓Fundamental rule
of conditional probability: 𝑃(𝐴|𝐵)=𝑃(𝐵|𝐴)*𝑃(𝐴) / 𝑃(𝐵)