CERTIFIED ANALYTICS
PROFESSIONAL EXAM – MODELING
Q&A
Stochastic Optimization - Answer-The process of maximizing or minimizing the value
of a mathematical or statistical function when one or more of the input parameters is
subject to randomness.
Simulation Optimization - Answer-The use of probability and statistics to model
uncertainty, combined with optimization techniques, to find good decisions in highly
complex and highly uncertain settings.
Predictive Modeling Techniques - Answer-Simulation - discrete event, monte carlo,
agent-based modeling
Regression - logistic, linear, stepwise
Statistical Inferences - confidence intervals, hypothesis testing, ANOVA,
experimental design
Classification
Clustering
AI
Game Theory
Monte Carlo Simulation - Answer-a risk analysis technique in which probable future
events are simulated on a computer, generating estimated rates of return and risk
indexes
Agent Based Modeling - Answer-Modeling complex phenomena as systems of
autonomous agents that follow relatively simple rules for interaction.
A system is modeled as a collection of autonomous decision-making entities called
agents. Each agent individually assesses its situation and makes decisions on the
basis of a set of rules.
Logistic regression - Answer-A type of regression model used to describe data and
to explain the relationship between one dependent binary variable and one or more
nominal, ordinal, interval or ratio-level independent variables.
Simplex Method - Answer-a popular algorithm for linear programming which begins
at a starting vertex and moves along the edges of the polytope until it reaches the
vertex of the optimal solution.
PROFESSIONAL EXAM – MODELING
Q&A
Stochastic Optimization - Answer-The process of maximizing or minimizing the value
of a mathematical or statistical function when one or more of the input parameters is
subject to randomness.
Simulation Optimization - Answer-The use of probability and statistics to model
uncertainty, combined with optimization techniques, to find good decisions in highly
complex and highly uncertain settings.
Predictive Modeling Techniques - Answer-Simulation - discrete event, monte carlo,
agent-based modeling
Regression - logistic, linear, stepwise
Statistical Inferences - confidence intervals, hypothesis testing, ANOVA,
experimental design
Classification
Clustering
AI
Game Theory
Monte Carlo Simulation - Answer-a risk analysis technique in which probable future
events are simulated on a computer, generating estimated rates of return and risk
indexes
Agent Based Modeling - Answer-Modeling complex phenomena as systems of
autonomous agents that follow relatively simple rules for interaction.
A system is modeled as a collection of autonomous decision-making entities called
agents. Each agent individually assesses its situation and makes decisions on the
basis of a set of rules.
Logistic regression - Answer-A type of regression model used to describe data and
to explain the relationship between one dependent binary variable and one or more
nominal, ordinal, interval or ratio-level independent variables.
Simplex Method - Answer-a popular algorithm for linear programming which begins
at a starting vertex and moves along the edges of the polytope until it reaches the
vertex of the optimal solution.
