## Statistics Minor

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

The minor complements major areas in mathematics, business, and the sciences.

#### Degree Requirements

**A. All of the following**

Please note: Students may take either M148 and M149, or M151

M148 Calculus I with Precalculus (part 1) (4 cr.)

This course, followed by M151 or courses equivalent to college algebra and college trigonometry.

M149 Calculus I with Precalculus (part 2) (4 cr.)

This course completes the two-semester sequence that begins with M151.

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 M149.

This course is a continuation of M151 are revisited at a higher mathematical level. Topics include: applications of the definite integral, techniques of integration, improper integrals, introduction to differential equations, numerical methods for integration and approximation, curves in the plane given parametrically, polar coordinates, and vectors in 2-space and 3-space.

This course continues the development of Calculus from M152. Topics include: sequences and series, and differentiation and integration of vector-valued functions and functions of several variables.

**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.

ST232 Introduction to Statistics (2 cr.)

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 ST132.

**C. Two of the following:**

ST350-359 Special Topics (3 cr.)

Selected topics in statistics may be offered depending on student interest.

ST371 Applied Regression Analysis (3 cr.)

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.

ST373 Design of Experiments (3 cr.)

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.

ST431 Mathematical Statistics (3 cr.)

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.

ST496/497 Statistics Internship (1–17 cr.)

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.