ISYE 6501 CORE MAIN QUESTIONS AND ANSWERS
SET A+
✔✔Multiplicative seasonality - ✔✔Seasonal effect that is multiplied by a baseline value
(for example, "the temperature in June is 20% higher than the annual baseline").
✔✔Multiplier - ✔✔A term that something is multiplied by. For example, to change units
from meters to centimeters, the multiplier is 100.
✔✔Negative likelihood ratio - ✔✔Ratio of the fraction of data points in a certain category
that are misclassified as not in the cateogry. equal to (1-sensitivity)/specificity =
𝐹𝐹⁄(𝐹𝐹+𝑇𝑇) 𝑇𝑇/(𝑇𝑇+𝐹𝐹).
✔✔Negative predictive value - ✔✔Fraction of data points classified as not in a certain
category that are really not in that category; equal to 𝑇𝑇/𝑇𝑇+𝐹𝐹.
✔✔Non-convex program - ✔✔Optimization model where the constraint set is not
convex, and/or the objective function is to minimize a nonconvex function or to
maximize a nonconcave function.
✔✔Non-negativity constraints - ✔✔Constraints that require variables to be greater than
or equal to zero.
✔✔Nonparametric test - ✔✔Statistical test that makes no assumptions about the
population distribution from which the data is sampled. Nonparametric tests often focus
on the median.
✔✔Norm/distance norm - ✔✔A function that measures the size/length of a vector. In
this course we focus on Minkowski norm (or p-norm).
✔✔Normal distribution - ✔✔Continuous probability distribution: 𝑓(𝑥) = 1 / 𝜎√2𝜋
𝑒𝑒−(𝑥−𝜇)2 2𝜎2 .
, ✔✔Objective function - ✔✔Part of an optimization model that measures the quality of a
solution (the values of the variables).
✔✔Observation - ✔✔(1) A measurement of one attribute of a data point. (2) A
measurement of all attributes of a data point. (3) The act of
watching/measuring/recording something.
✔✔Optimal - ✔✔Best possible, while satisfying all constraints.
✔✔Optimal solution - ✔✔A solution that satisfies a set of constraints, and has the best-
possible objective value.
✔✔Optimization - ✔✔Finding the values of variables/decisions that yield the best value
of an objective function while satisfying a set of constraints (restrictions).
✔✔Order of magnitude - ✔✔The relative size of something, often denoted by multiples
of 10. a 2-digit number is one order of magnitude smaller than a 3-digit number
✔✔Orthogonal - ✔✔At right angles to one another.
✔✔Outcome - ✔✔A variable of interest that a model tries to estimate or predict.
✔✔Outlier - ✔✔A data point or set of points that's far from the rest in one way or
another (see point outlier, contextual outlier, collective outlier).
✔✔Overfitting - ✔✔Building a model that describes random effects instead of or in
significant addition to the real effects. Overfitted models will have high prediction errors.
✔✔Parameter - ✔✔A constant whose value determines something about a system.
✔✔Parametric test - ✔✔Statistical test that assumes the data being tested is sampled
from a distribution governed by certain parameter(s). Often focused on the mean.
✔✔PCA - ✔✔Principal component analysis.
✔✔Perturbation - ✔✔A change (usually small) from the actual or expected value of
something.
✔✔𝑝-norm - ✔✔Measures vector length similar to the Minkowski distance of order 𝑝.
✔✔Point outlier - ✔✔A data point that is (uncommonly) far from other data points.
SET A+
✔✔Multiplicative seasonality - ✔✔Seasonal effect that is multiplied by a baseline value
(for example, "the temperature in June is 20% higher than the annual baseline").
✔✔Multiplier - ✔✔A term that something is multiplied by. For example, to change units
from meters to centimeters, the multiplier is 100.
✔✔Negative likelihood ratio - ✔✔Ratio of the fraction of data points in a certain category
that are misclassified as not in the cateogry. equal to (1-sensitivity)/specificity =
𝐹𝐹⁄(𝐹𝐹+𝑇𝑇) 𝑇𝑇/(𝑇𝑇+𝐹𝐹).
✔✔Negative predictive value - ✔✔Fraction of data points classified as not in a certain
category that are really not in that category; equal to 𝑇𝑇/𝑇𝑇+𝐹𝐹.
✔✔Non-convex program - ✔✔Optimization model where the constraint set is not
convex, and/or the objective function is to minimize a nonconvex function or to
maximize a nonconcave function.
✔✔Non-negativity constraints - ✔✔Constraints that require variables to be greater than
or equal to zero.
✔✔Nonparametric test - ✔✔Statistical test that makes no assumptions about the
population distribution from which the data is sampled. Nonparametric tests often focus
on the median.
✔✔Norm/distance norm - ✔✔A function that measures the size/length of a vector. In
this course we focus on Minkowski norm (or p-norm).
✔✔Normal distribution - ✔✔Continuous probability distribution: 𝑓(𝑥) = 1 / 𝜎√2𝜋
𝑒𝑒−(𝑥−𝜇)2 2𝜎2 .
, ✔✔Objective function - ✔✔Part of an optimization model that measures the quality of a
solution (the values of the variables).
✔✔Observation - ✔✔(1) A measurement of one attribute of a data point. (2) A
measurement of all attributes of a data point. (3) The act of
watching/measuring/recording something.
✔✔Optimal - ✔✔Best possible, while satisfying all constraints.
✔✔Optimal solution - ✔✔A solution that satisfies a set of constraints, and has the best-
possible objective value.
✔✔Optimization - ✔✔Finding the values of variables/decisions that yield the best value
of an objective function while satisfying a set of constraints (restrictions).
✔✔Order of magnitude - ✔✔The relative size of something, often denoted by multiples
of 10. a 2-digit number is one order of magnitude smaller than a 3-digit number
✔✔Orthogonal - ✔✔At right angles to one another.
✔✔Outcome - ✔✔A variable of interest that a model tries to estimate or predict.
✔✔Outlier - ✔✔A data point or set of points that's far from the rest in one way or
another (see point outlier, contextual outlier, collective outlier).
✔✔Overfitting - ✔✔Building a model that describes random effects instead of or in
significant addition to the real effects. Overfitted models will have high prediction errors.
✔✔Parameter - ✔✔A constant whose value determines something about a system.
✔✔Parametric test - ✔✔Statistical test that assumes the data being tested is sampled
from a distribution governed by certain parameter(s). Often focused on the mean.
✔✔PCA - ✔✔Principal component analysis.
✔✔Perturbation - ✔✔A change (usually small) from the actual or expected value of
something.
✔✔𝑝-norm - ✔✔Measures vector length similar to the Minkowski distance of order 𝑝.
✔✔Point outlier - ✔✔A data point that is (uncommonly) far from other data points.
