Mathematics of Industry and Government (2017)

Deterministic Decision Making

Probabilistic Decision Making

Students will explore decision making through linear programming, optimal locations, and optimal paths.

Students will use normal and other (e.g.binomial, geometric, and Poisson) distributions as well as simulations to make appropriate decisions.

Students will use advanced linear programming to make decisions.

Students will determine optimal locations and use them to make appropriate decisions.

Students will determine optimal paths and use them to make appropriate decisions.

Students will use properties of normal distributions to make decisions about optimization and efficiency.

Students will use properties of other distributions (e.g. binomial, geometric, Poisson) to make decisions about optimization and efficiency.

Students will use other probabilistic models to make decisions.

Students will use computer simulations to make decisions.

Distinguish among continuous, integer, and binary contexts.

Model a contextual problem with three or more variables.

Solve problems with three or more variables using technology.

Interpret the results.

Examine cause and effect of contextual changes.

Find the optimal median location in a one-dimensional context.

Find the optimal median location in a rectilinear context.

Find the optimal location given three equally weighted, non-collinear points. d. Find the optimal location in a set covering context.

Relate context to a network representation.

Apply appropriate recursive algorithms for minimum spanning tree, shortest path, and critical path management.

Examine alternate decisions in response to contextual changes.

Calculate theoretical and empirical probabilities using standardized and non-standardized data.

Analyze and interpret the probabilities in terms of context.

Consider contextual factors and investigate issues within the decision-making process.

Apply techniques to quality control settings.

Calculate theoretical and empirical probabilities using standardized and non-standardized data.

Analyze and interpret the probabilities in terms of context.

Consider contextual factors and investigate issues within the decision-making process.

Use program evaluation review technique (PERT) to investigate completion times of a project.

Develop and apply transition matrices to make predictions using Markov Chains.

Apply queuing theory.

Consider contextual factors and investigate issues within the decision making process.

Use technology to simulate a real-world situation.

Analyze, evaluate, and interpret results.

Examine alternate decisions in response to contextual changes.