ISYE 6501 FINAL EXAM & QUIZ: UPDATED
QUESTIONS AND ANSWERS — 100%
ACCURATE AND RELIABLE
1-norm
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
testing two alternatives to see which one performs better
2-norm
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
Fraction of data points correctly classified by a model; equal to TP+TN / TP+FP+TN+FN
Action
In ARENA, something that is done to an entity.
Additive Seasonality
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
Variant of R2 that encourages simpler models by penalizing the use of too many variables.
AIC
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
Step-by-step procedure designed to carry out a task.
Analysis of Variance/ANOVA
Statistical method for dividing the variation in observations among different sources.
Approximate dynamic program
Dynamic programming model where the value functions are approximated.
Arc
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)
Area under the ROC curve; an estimate of the classification model's accuracy. Also called concordance
index.
ARIMA
Autoregressive integrated moving average.
Arrival Rate
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
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
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
Regression technique using past values of time series data as predictors of future values.
Autoregressive integrated moving average (ARIMA)
Time series model that uses differences between observations when data is nonstationary. Also called
Box-Jenkins.
Backward elimination
, Variable selection process that starts with all variables and then iteratively removes the least-
immediately-relevant variables from the model.
Balanced Design
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
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
Fundamental rule of conditional probability: 𝑃(𝐴|𝐵)=𝑃(𝐵|𝐴)*𝑃(𝐴) / 𝑃(𝐵)
Bayesian Information criterion (BIC)
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
Regression model that incorporates estimates of how coefficients and error are distributed.
Bellman's Equation
Equation used in dynamic programming that ensures optimality of a solution.
Bernoulli Distribution
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
Systematic difference between a true parameter of a population and its estimate.
Binary Data
Data that can take only two different values (true/false, 0/1, black/white, on/off, etc.)
Binary integer program
Integer program where all variables are binary variables.
Binary Variable
Variable that can take just two values: 0 and 1.
Binomial Distribution
QUESTIONS AND ANSWERS — 100%
ACCURATE AND RELIABLE
1-norm
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
testing two alternatives to see which one performs better
2-norm
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
Fraction of data points correctly classified by a model; equal to TP+TN / TP+FP+TN+FN
Action
In ARENA, something that is done to an entity.
Additive Seasonality
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
Variant of R2 that encourages simpler models by penalizing the use of too many variables.
AIC
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
Step-by-step procedure designed to carry out a task.
Analysis of Variance/ANOVA
Statistical method for dividing the variation in observations among different sources.
Approximate dynamic program
Dynamic programming model where the value functions are approximated.
Arc
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)
Area under the ROC curve; an estimate of the classification model's accuracy. Also called concordance
index.
ARIMA
Autoregressive integrated moving average.
Arrival Rate
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
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
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
Regression technique using past values of time series data as predictors of future values.
Autoregressive integrated moving average (ARIMA)
Time series model that uses differences between observations when data is nonstationary. Also called
Box-Jenkins.
Backward elimination
, Variable selection process that starts with all variables and then iteratively removes the least-
immediately-relevant variables from the model.
Balanced Design
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
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
Fundamental rule of conditional probability: 𝑃(𝐴|𝐵)=𝑃(𝐵|𝐴)*𝑃(𝐴) / 𝑃(𝐵)
Bayesian Information criterion (BIC)
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
Regression model that incorporates estimates of how coefficients and error are distributed.
Bellman's Equation
Equation used in dynamic programming that ensures optimality of a solution.
Bernoulli Distribution
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
Systematic difference between a true parameter of a population and its estimate.
Binary Data
Data that can take only two different values (true/false, 0/1, black/white, on/off, etc.)
Binary integer program
Integer program where all variables are binary variables.
Binary Variable
Variable that can take just two values: 0 and 1.
Binomial Distribution
