1-norm - ANS Similar to rectilinear distance; measures the sum of the lengths of each
dimension of a vector from the origin. If 𝑧𝑧 = (𝑧𝑧1, 𝑧𝑧2, ... , 𝑧𝑧𝑚𝑚) is a vector in an 𝑚𝑚-dimensional
space, then its 1-norm is �|𝑧𝑧1|1 + |𝑧𝑧2|1 + ⋯ + |𝑧𝑧𝑚𝑚| 1 1 = |𝑧𝑧1| + |𝑧𝑧2| + ⋯ + |𝑧𝑧| = ∑ |𝑧𝑧𝑖𝑖| 𝑚𝑚
𝑖𝑖=1 .
2-norm - ANS Similar to Euclidian distance; measures the straight-line length of a vector
from the origin. If 𝑧𝑧 = (𝑧𝑧1, 𝑧𝑧2, ... , 𝑧𝑧𝑚𝑚) is a vector in an 𝑚𝑚- dimensional space, then its
2-norm is �(𝑧𝑧1)2 + (𝑧𝑧2)2 + ⋯ + (𝑧𝑧𝑚𝑚)2 2 = �∑ (𝑧𝑧𝑖𝑖) 𝑚𝑚 2 𝑖𝑖=1 2 .
A/B testing - ANS Test of two alternatives to see if either one leads to better outcomes.
Accuracy - ANS Fraction of data points correctly classified by a model; equal to 𝑇𝑇𝑇𝑇+𝑇𝑇𝑇𝑇
𝑇𝑇𝑇𝑇+𝐹𝐹𝐹𝐹+𝑇𝑇𝑇𝑇+𝐹𝐹𝐹𝐹.
Action - ANS In ARENA, something that is done to an entity.
Additive seasonality - ANS 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/Adjusted R2 - ANS Variant of R2 that encourages simpler models by
penalizing the use of too many variables
AIC - ANS Akaike information criterion
Akaike information criterion (AIC) - ANS 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 - ANS Step-by-step procedure designed to carry out a task.
Analysis of Variance/ANOVA - ANS Statistical method for dividing the variation in
observations among different sources.
Approximate dynamic program - ANS Dynamic programming model where the value
functions are approximated.
,Arc - ANS 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 curve/AUC - ANS Area under the ROC curve; an estimate of the classification
model's accuracy. Also called concordance index.
ARIMA - ANS Autoregressive integrated moving average.
Arrival rate - ANS 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 - ANS 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 - ANS 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 - ANS Regression technique using past values of time series data as
predictors of future values.
Autoregressive integrated moving average (ARIMA) - ANS Time series model that uses
differences between observations when data is nonstationary. Also called Box-Jenkins
Backward elimination - ANS Variable selection process that starts with all variables and
then iteratively removes the least-immediately-relevant variables from the model.
Balanced design - ANS 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 - ANS 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 - ANS Fundamental rule of conditional probability: 𝑃𝑃(𝐴𝐴|𝐵𝐵) =
𝑃𝑃(𝐵𝐵|𝐴𝐴)𝑃𝑃(𝐴𝐴) 𝑃𝑃(𝐵𝐵) .
Bayesian Information criterion (BIC) - ANS 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 - ANS Regression model that incorporates estimates of how
coefficients and error are distributed.
, Bellman's equation - ANS Equation used in dynamic programming that ensures optimality
of a solution.
Bernoulli distribution - ANS 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 𝑝𝑝 and the probability of outcome being 0 is 𝑞𝑞 = 1 − 𝑝𝑝, where 𝑝𝑝 is
between 0 and 1.
Bias - ANS Systematic difference between a true parameter of a population and its
estimate
BIC - ANS Bayesian information criterion
Binary data - ANS Data that can take only two different values (true/false, 0/1, black/white,
on/off, etc.).
Binary integer program - ANS Integer program where all variables are binary variables.
Binary variable - ANS Variable that can take just two values: 0 and 1.
Binomial distribution - ANS Discrete probability distribution for the exact number of
successes, k, out of a total of n iid Bernoulli trials, each with probability p: Pr(𝑘𝑘) = � 𝑛𝑛 𝑘𝑘�
𝑝𝑝𝑘𝑘(1 − 𝑝𝑝)𝑛𝑛−𝑘𝑘.
Blocking - ANS Factor introduced to an experimental design that interacts with the effect of
the factors to be studied. The effect of the factors is studied within the same level (block) of the
blocking factor
Box and whisker plot - ANS Graphical representation data showing the middle range of
data (the "box"), reasonable ranges of variability ("whiskers"), and points (possible outliers)
outside those ranges.
Box-Cox transformation - ANS Transformation of a non-normally-distributed response to a
normal distribution.
Branching - ANS Splitting a set of data into two or more subsets, to each be analyzed
separately.
CART - ANS Classification and regression trees.
Change detection - ANS Identifying when a significant change has taken place in a
process.
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