Equivalency Details

3 credits Prerequisite: High school mathematics through intermediate algebra. Not recommended for majors in mathematics or computer science. Introduction to probability theory, random variables, and probability distributions. Statistics and sampling distributions; testing hypotheses and estimating parameters.

This course provides a solid introduction to probability theory and its applications as well as the visual and mathematical analysis of data and data distributions. This course is similar to Modern College Mathematics (MAT 120) in design and can be used as mathematics elective for students who are not science, engineering, or mathematics majors. It may be taken before Modern College Mathematics. It also serves as a prerequisite for MAT 210. Upon successful completion of this course, students should be able to: Apply techniques and formulas to solve problems involving the fundamental counting principle, permutations and combinations; Use the definitions, axioms, and theorems of probability to solve problems; Use statistical measures, graphs, and normality to organize, describe, visually represent, and analyze data; Solve problems involving the simple linear regression line model and the correlation coefficient; Use a software package to solve problems in the competencies covered.