age 1 of 76
ISYE 6501 MIDTERM 2 EXAM STUDY GUIDE 2025/2026
ACCURATE QUESTIONS AND CORRECT DETAILED
ANSWERS WITH RATIONALES || 100% GUARANTEED
PASS <BRAND NEW VERSION>
Area under the curve (AUC) ......ANSWER........Area under the
ROC curve; an estimate of the classification model's accuracy.
Also called concordance index.
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.
,age 2 of 76
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.
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
,age 3 of 76
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)
Bayesian Information criterion (BIC) ......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.
, age 4 of 76
Bayesian Regression ......ANSWER........Regression model that
incorporates estimates of how coefficients and error are
distributed.
Bellman's Equation ......ANSWER........Equation used in dynamic
programming that ensures optimality of a solution.
Bernoulli Distribution ......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 ......ANSWER........Systematic difference between a true
parameter of a population and its estimate.
Binary Data ......ANSWER........Data that can take only two
different values (true/false, 0/1, black/white, on/off, etc.)
ISYE 6501 MIDTERM 2 EXAM STUDY GUIDE 2025/2026
ACCURATE QUESTIONS AND CORRECT DETAILED
ANSWERS WITH RATIONALES || 100% GUARANTEED
PASS <BRAND NEW VERSION>
Area under the curve (AUC) ......ANSWER........Area under the
ROC curve; an estimate of the classification model's accuracy.
Also called concordance index.
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.
,age 2 of 76
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.
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
,age 3 of 76
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)
Bayesian Information criterion (BIC) ......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.
, age 4 of 76
Bayesian Regression ......ANSWER........Regression model that
incorporates estimates of how coefficients and error are
distributed.
Bellman's Equation ......ANSWER........Equation used in dynamic
programming that ensures optimality of a solution.
Bernoulli Distribution ......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 ......ANSWER........Systematic difference between a true
parameter of a population and its estimate.
Binary Data ......ANSWER........Data that can take only two
different values (true/false, 0/1, black/white, on/off, etc.)
