Descriptive statistics, elements of probability theory, and basic ideas of statistical inference. Topics include frequency distributions, measures of central tendency and dispersion, commonly occurring distributions (binomial, normal, etc.), estimation, and testing of hypotheses. Prerequisite: high school algebra. (Gen.Ed. R2)

[Note: Because this course presupposes knowledge of basic math skills, it will satisfy the R1 requirement upon successful completion.]

Descriptive statistics, elements of probability theory, and basic ideas of statistical inference. Topics include frequency distributions, measures of central tendency and dispersion, commonly occurring distributions (binomial, normal, etc.), estimation, and testing of hypotheses. Prerequisite: high school algebra. (Gen.Ed. R2)

[Note: Because this course presupposes knowledge of basic math skills, it will satisfy the R1 requirement upon successful completion.]

Descriptive statistics, elements of probability theory, and basic ideas of statistical inference. Topics include frequency distributions, measures of central tendency and dispersion, commonly occurring distributions (binomial, normal, etc.), estimation, and testing of hypotheses. Prerequisite: high school algebra. (Gen.Ed. R2)

[Note: Because this course presupposes knowledge of basic math skills, it will satisfy the R1 requirement upon successful completion.]

Not available at this time

Introduction to the field of applied behavior analysis applied to education (conceptual foundations, methodology, applications).

Basic concepts of linear algebra. Matrices, determinants, systems of linear equations, vector spaces, linear transformations, and eigenvalues. Prerequisite or corequisite: MATH 132, or 136, or consent of instructor. (Gen.Ed. R2)

[Note: Because this course presupposes knowledge of basic math skills, it will satisfy the R1 requirement upon successful completion.]

Formerly MTH 247. Theory and applications of regression techniques; linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Prerequisite: one of the following: MTH 201/PSY 201, GOV 190, MTH 219, MTH 220, ECO 220, or the equivalent or a score of 4 or 5 on the AP Statistics examination. Enrollment limited to 25.

There are many factors today that require businesses to play a role in the success of society. Through this class we hope to develop a standard of "Citizens First" were Isenberg School students will participate in positive efforts toward improving the well-being of others by contributing to our local, University, and global communities. The goal is for future business leaders to understand that Community Matters and Character Counts.