Applied Math
Applied Math is a combination of theories and techniques, such as mathematical modeling and computational methods, to formulate and solve practical problems in business, engineering, and technology.
This core competency area includes an understanding of Probability, Probability Distributions, Baye's theorem, Dependent & Independent events, Combinatorics, Linear Algebra, Matrices, and Vectors.
Key Competencies:
- Probability - An understanding of random variables, expected value, and conditional probability.
- Probability Distributions - An understanding of Distributions and their real world implications including but not limited to Normal Distributions, Standard Normal Distributions, Exponential Distributions, Poisson Distributions, Gamma Distributions, Log-Normal Distributions etc.
- Baye's theorem - An understanding of and ability to use Bayes theorem, which provides a way to calculate the probability of a hypothesis based on its prior probability, the probabilities of observing various data, and so on.
- Dependent & Independent events - Ability to work with Dependent and & Independent events. Dependent influence the probability of other events – or their probability of occurring is affected by other events. Independent events do not affect one another and do not increase or decrease the probability of another event happening.
- Combinations & Permutations - An understanding of Combinations & Permutations, and how to determine the probability of occurrence using Combinatorics.
- Linear Algebra - An understanding of Linear Algebra, and representations in vector spaces and through matrices.
- Matrices - Ability to use matrices, and understanding of matrix properties, operations, among other aspects.
- Solutions of equations - Familiarity with solving for unknowns using mathematical models.
- Vectors - An understanding of Vectors and their common operations (dot product, cross product, resultant).