The statistics minor is designed to give students in a variety of majors a career-enhancing introduction to the application and theory of statistics.
In a world that is increasingly dependent upon data, the ability to analyze, interpret, and communicate the findings of information is essential. in addition, a foundation in statistics also helps students who plan to attend graduate school, providing a broad introduction to interpreting research results. No matter a student's post-graduate plans, developing decision-making skills that are grounded in fact is extraordinarily valuable.
High School Preparation
Statistics; Mathematics; Business; Physics; Chemistry; Biology
Enhance Your Experience
A. All of the following
(either M148 & M149 or M151):
This course, followed by
This course completes the two-semester sequence that begins with
This course provides an introduction to the differential and integral calculus. Topics include: the concepts of function, limit, continuity, derivative, definite and indefinite integrals, and an introduction to transcendental functions. Credit is not granted for this course and
This course is a continuation of
This course continues the development of Calculus from
B. Both of the following:
This calculus-based course is designed to provide mathematics majors and minors with an introduction to the mathematical underpinnings of statistics. Topics include: probability axioms, probability, Bayes' Theorem, random variables, discrete and continuous probability distributions, and expected value.
This course is designed to provide the basic ideas and techniques of statistics. Topics include: descriptive and inferential statistics, an intuitive introduction to probability, estimation, hypothesis testing, chi-square tests, regression and correlation. This course makes significant use of appropriate technology. Topics in this course are treated at a higher mathematical level than they are treated in
C. Two statistics courses of the following:
Selected topics in statistics may be offered depending on student interest.
This course provides students with an introduction to linear and non-linear models in statistics. Topics include: linear regression, multiple regression, one-, two-, and higher-way analysis of variance, and popular experimental designs. Real-world problems are analyzed using appropriate technology.
This course provides an introduction to the principles of the design of experiments from a statistical perspective. Topics include: Analysis of variance, covariance, randomization, completely randomized, randomized block, Latin-square, factorial, response surface methods and other designs.
This course provides a mathematical treatment of probability and statistics. Topics include: several descriptions of the concept of probability, univariate and bivariate probability distributions, joint and marginal probability distributions, covariance, hypothesis testing, estimation, data analysis, and sampling distributions.
This opportunity provides the student with experience and training in statistical techniques. The internship must be approved by the department chair and, depending on the nature of the internship, may be counted towards the major. Students usually are expected to give a presentation following the experience.