Isye 6501 Final EXAM NEWEST 2025-2026
COMPLETE QUESTIONS AND CORRECT
DETAILED ANSWERS (VERIFIED ANSWERS)
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VERSION!!
Algorithm - CORRECT ANSWER- Step-by-step procedure designed to carry out a task.
Analysis of Variance/ANOVA - CORRECT ANSWER- Statistical method for dividing the variation in
observations among different sources.
Approximate dynamic program - CORRECT ANSWER- Dynamic programming model where the
value functions are approximated.
Arc - CORRECT 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) - CORRECT ANSWER- Area under the ROC curve; an estimate of the
classification model's accuracy. Also called concordance index.
,ARIMA - CORRECT ANSWER- Autoregressive integrated moving average.
Arrival Rate - CORRECT 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 - CORRECT 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 - CORRECT 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.
Autoregression - CORRECT ANSWER- Regression technique using past values of time series data
as predictors of future values.
1-norm - CORRECT 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|
A/B Testing - CORRECT ANSWER- testing two alternatives to see which one performs better
2-norm - CORRECT 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)
Accuracy - CORRECT ANSWER- Fraction of data points correctly classified by a model; equal to
TP+TN / TP+FP+TN+FN
Action - CORRECT ANSWER- In ARENA, something that is done to an entity.
,Additive Seasonality - CORRECT 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 - CORRECT ANSWER- Variant of R2 that encourages simpler models by
penalizing the use of too many variables.
AIC - CORRECT 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.
Autoregressive integrated moving average (ARIMA) - CORRECT ANSWER- Time series model that
uses differences between observations when data is nonstationary. Also called Box-Jenkins.
Backward elimination - CORRECT ANSWER- Variable selection process that starts with all
variables and then iteratively removes the least-immediately-relevant variables from the
model.
Balanced Design - CORRECT 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 - CORRECT 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 - CORRECT ANSWER- Fundamental rule of conditional probability:
𝑃(𝐴|𝐵)=𝑃(𝐵|𝐴)*𝑃(𝐴) / 𝑃(𝐵)
Bayesian Information criterion (BIC) - CORRECT ANSWER- Model selection technique that trades
off model fit and model complexity. When comparing models, the model with lower BIC is
preferred. Generally penalizes complexity more than AIC.
, Bayesian Regression - CORRECT ANSWER- Regression model that incorporates estimates of how
coefficients and error are distributed.
Bellman's Equation - CORRECT ANSWER- Equation used in dynamic programming that ensures
optimality of a solution.
Bernoulli Distribution - CORRECT ANSWER- Discrete probability distribution where the outcome
is binary, either 0 or 1. Often, 1 represents success and 0 represents failure. The probability of
the outcome being 1 is 𝑝 and the probability of outcome being 0 is 𝑞 = 1−𝑝, where 𝑝 is between
0 and 1.
Bias - CORRECT ANSWER- Systematic difference between a true parameter of a population and
its estimate.
Binary Data - CORRECT ANSWER- Data that can take only two different values (true/false, 0/1,
black/white, on/off, etc.)
Binary integer program - CORRECT ANSWER- Integer program where all variables are binary
variables.
Binary Variable - CORRECT ANSWER- Variable that can take just two values: 0 and 1.
Binomial Distribution - CORRECT ANSWER- Discrete probability distribution for the exact number
of successes, k, out of a total of n iid Bernoulli trials, each with probability p: Pr(𝑘)= (n over k)
p^k(1-p)^n-k
COMPLETE QUESTIONS AND CORRECT
DETAILED ANSWERS (VERIFIED ANSWERS)
|ALREADY GRADED A+||BRAND NEW
VERSION!!
Algorithm - CORRECT ANSWER- Step-by-step procedure designed to carry out a task.
Analysis of Variance/ANOVA - CORRECT ANSWER- Statistical method for dividing the variation in
observations among different sources.
Approximate dynamic program - CORRECT ANSWER- Dynamic programming model where the
value functions are approximated.
Arc - CORRECT 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) - CORRECT ANSWER- Area under the ROC curve; an estimate of the
classification model's accuracy. Also called concordance index.
,ARIMA - CORRECT ANSWER- Autoregressive integrated moving average.
Arrival Rate - CORRECT 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 - CORRECT 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 - CORRECT 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.
Autoregression - CORRECT ANSWER- Regression technique using past values of time series data
as predictors of future values.
1-norm - CORRECT 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|
A/B Testing - CORRECT ANSWER- testing two alternatives to see which one performs better
2-norm - CORRECT 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)
Accuracy - CORRECT ANSWER- Fraction of data points correctly classified by a model; equal to
TP+TN / TP+FP+TN+FN
Action - CORRECT ANSWER- In ARENA, something that is done to an entity.
,Additive Seasonality - CORRECT 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 - CORRECT ANSWER- Variant of R2 that encourages simpler models by
penalizing the use of too many variables.
AIC - CORRECT 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.
Autoregressive integrated moving average (ARIMA) - CORRECT ANSWER- Time series model that
uses differences between observations when data is nonstationary. Also called Box-Jenkins.
Backward elimination - CORRECT ANSWER- Variable selection process that starts with all
variables and then iteratively removes the least-immediately-relevant variables from the
model.
Balanced Design - CORRECT 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 - CORRECT 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 - CORRECT ANSWER- Fundamental rule of conditional probability:
𝑃(𝐴|𝐵)=𝑃(𝐵|𝐴)*𝑃(𝐴) / 𝑃(𝐵)
Bayesian Information criterion (BIC) - CORRECT ANSWER- Model selection technique that trades
off model fit and model complexity. When comparing models, the model with lower BIC is
preferred. Generally penalizes complexity more than AIC.
, Bayesian Regression - CORRECT ANSWER- Regression model that incorporates estimates of how
coefficients and error are distributed.
Bellman's Equation - CORRECT ANSWER- Equation used in dynamic programming that ensures
optimality of a solution.
Bernoulli Distribution - CORRECT ANSWER- Discrete probability distribution where the outcome
is binary, either 0 or 1. Often, 1 represents success and 0 represents failure. The probability of
the outcome being 1 is 𝑝 and the probability of outcome being 0 is 𝑞 = 1−𝑝, where 𝑝 is between
0 and 1.
Bias - CORRECT ANSWER- Systematic difference between a true parameter of a population and
its estimate.
Binary Data - CORRECT ANSWER- Data that can take only two different values (true/false, 0/1,
black/white, on/off, etc.)
Binary integer program - CORRECT ANSWER- Integer program where all variables are binary
variables.
Binary Variable - CORRECT ANSWER- Variable that can take just two values: 0 and 1.
Binomial Distribution - CORRECT ANSWER- Discrete probability distribution for the exact number
of successes, k, out of a total of n iid Bernoulli trials, each with probability p: Pr(𝑘)= (n over k)
p^k(1-p)^n-k
