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Examen

Exam (elaborations) GT ISYE 6501

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GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version! GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand New Version!

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Institución
GT ISYE 6501
Grado
GT ISYE 6501

Información del documento

Subido en
28 de julio de 2025
Número de páginas
53
Escrito en
2024/2025
Tipo
Examen
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Preguntas y respuestas

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7/28/25, 11:12 PM GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand…




GT ISYE 6501 Final Exam 2025 (Actual Exam) |
Complete Questions and Correct Answers | Graded
A+ | Verified Answers | Brand New Version!




Similar to rectilinear 1-norm
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|
testing two alternatives to A/B Testing
see which one performs
better
Similar to Euclidian distance; 2-norm
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)
Fraction of data points Accuracy
correctly classified by a
model; equal to TP+TN /
TP+FP+TN+FN
… 1/53

,7/28/25, 11:12 PM GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand…

In ARENA, something that is Action
done to an entity.
Seasonal effect that is Additive Seasonality
added to a baseline value
(for example, "the
temperature in June is 10
degrees above the annual
baseline").
Variant of R2 that Adjusted R-squared
encourages simpler models
by penalizing the use of too
many variables.
Akaike information criterion- AIC
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.
Step-by-step procedure Algorithm
designed to carry out a
task.
Statistical method for Analysis of Variance/ANOVA
dividing the variation in
observations among
different sources.
Dynamic programming Approximate dynamic program
model where the value
functions are approximated.
Connection between two Arc
nodes/vertices in a network.
In a network model, there is
a variable for each arc,
equal to the amount of flow
… 2/53

,7/28/25, 11:12 PM GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand…

on the arc, and (optionally)
a
capacity constraint on the
arc's flow. Also called an
edge.
Area under the ROC curve; Area under the curve (AUC)
an estimate of the
classification model's
accuracy. Also
called concordance index.
Autoregressive integrated ARIMA
moving average.
Expected number of arrivals Arrival Rate
of people, things, etc. per
unit time -- for example, the
expected number of truck
deliveries per
hour to a warehouse.
Network optimization Assignment Problem
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.
A characteristic or Attribute
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.
Regression technique using Autoregression
past values of time series
data as predictors of future
values.



… 3/53

, 7/28/25, 11:12 PM GT ISYE 6501 Final Exam 2025 (Actual Exam) | Complete Questions and Correct Answers | Graded A+ | Verified Answers | Brand…

Time series model that uses Autoregressive integrated moving average (ARIMA)
differences between
observations when data is
nonstationary. Also called
Box-Jenkins.
Variable selection process Backward elimination
that starts with all variables
and then iteratively
removes the least-
immediately-relevant
variables
from the model.
Set of combinations of Balanced Design
factor values across multiple
factors, that has the same
number of runs for all
combinations of levels of
one or more factors.
An entity arrives to the Balking
queue, sees the size of the
line (or some other
attribute), and decides to
leave the system.
Fundamental rule of Bayes' theorem/Bayes' rule
conditional
probability:
𝑃(𝐴|𝐵)=𝑃(𝐵|𝐴)*𝑃(𝐴) / 𝑃(𝐵)
Model selection technique Bayesian Information criterion (BIC)
that trades off model fit and
model complexity. When
comparing models, the
model with lower BIC is
preferred. Generally
penalizes
complexity more than AIC.
Regression model that Bayesian Regression
incorporates
estimates of how
coefficients and error are
… 4/53
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