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ISYE 6501 Exam Bundle | Midterm 1, Midterm 2, and Final Exam | Introduction to Analytics Modeling | Georgia Institute of Technology

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ISYE 6501 Exam Bundle | Midterm 1, Midterm 2, and Final Exam | Introduction to Analytics Modeling | Georgia Institute of Technology

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ISYE 6501 Exam Bundle | Midterm 1, Midterm 2, and Final Exam |
Introduction to Analytics Modeling | Georgia Institute of Technology

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.



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.

, 2




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.



Autoregressive integrated moving average (ARIMA) - (CORRECT ANSWER)Time series model that uses
differences between observations when data is nonstationary. Also called Box-Jenkins.

, 3



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.

, 4



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



Blocking - (CORRECT ANSWER)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 - (CORRECT ANSWER)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 - (CORRECT ANSWER)Transformation of a non-normally-distributed response to
a normal distribution.



Branching - (CORRECT ANSWER)Splitting a set of data into two or more subsets, to each be analyzed
separately.



CART - (CORRECT ANSWER)Classification and regression trees.



Categorical Data - (CORRECT ANSWER)Data that classifies observations without quantitative meaning
(for example, colors of cars) or where quantitative amounts are categorized (for example, "0-10, 11-20,
...").

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