College of Natural and Health Sciences

School of Mathematical Sciences

Please note: All students are required to complete a web-based placement assessment called ALEKS to determine readiness for entry-level mathematics and statistics courses unless they meet certain exceptions. These exceptions are based on various factors such as SAT or ACT scores or previously earned mathematics credit in college-level courses or developmental education courses at a community college. Please see the Exceptions page at the UNC Math Placement website for complete details. Entry-level mathematics and statistics courses that require the ALEKS assessment include MATH 120, MATH 124, MATH 125, MATH 127, MATH 131, MATH 171, and STAT 150. More information on ALEKS and a link to the assessment can be found at http://www.unco.edu/nhs/mathsci/undergrad/placement/placement.html.

STAT 111 Introduction to Data Science

Introduction to elements of Data Science and elementary tools, programming languages, and techniques for data collection, visualization, computations, and inference. Includes ethical issues with data collection and analysis.
3

Prerequisites

(ALEKS Test Score with a minimum score of 025 or Completion of LC2-Mathematics course or Completion of LAX1-Mathematics course)

LAX1-Mathematics

STAT 149 Supplemental Statistics

In this supplementary course we will develop critical thinking, ethical decision-making, and effective communication. The course will provide supplemental academic support for students enrolled in Introduction to Statistical Analysis (STAT 150). This will include content review, study skills, and effective strategies for success in STAT 150. S/U graded.
1

STAT 150

Repeatable Status

Course is repeatable with no limitations

Course Fee

Differential Tuition Required

STAT 150 Introduction to Statistical Analysis

Prerequisite: Two years of high school algebra with a grade of C or better. Study techniques used in organizing data, including frequency distributions, histograms, measures of central tendency, measures of dispersion, probability distributions, point estimation, interval estimation and testing hypotheses.
3

Course Attribute

LAX1-Mathematics and GT Mathematics

STAT 202 Data Visualization

Provides tools to prepare data, critique and improve visualizations of statistical data, learn visual encoding principles of quantitative information, and learn how these principles are applied to create effective visualizations.
3

Prerequisites

STAT 150 with a minimum grade of C

Course Fee

Differential Tuition Required

STAT 250 Statistics for Life Sciences

This course is an introduction to statistical methods in biological sciences. Topics include study designs, data visualization and exploration, basic probability with applications, and statistical inference for comparing multiple groups.
3

Course Fee

Differential Tuition Required

STAT 355 Introduction to Applied Statistics and Probability

Introduces conceptions of statistics, data analysis, and concepts of probability. Focus is on understanding variability and probability, sampling and random variables, descriptive and inferential statistics.
3

Prerequisites

Concurrent Prerequisite MATH 132 with a minimum grade of C

Course Fee

Differential Tuition Required

STAT 406 Multiple Linear Regression

Topics in multiple linear regression, estimation of model parameters, inferences, diagnostics, model assumptions, ANOVA formulation.
3

Prerequisites

(MATH 350 or STAT 355 with a minimum grade of D-) or (STAT 150 and MATH 131 with a minimum grade of D-)

Course Fee

Differential Tuition Required

STAT 409 Sampling Techniques

Introduction to elementary sampling concepts. Includes random sampling, stratified sampling, cluster sampling and systematic sampling. Inferences and assumptions are presented for all sampling methods.
3

Prerequisites

(MATH 350 or STAT 355 with a minimum grade of D-) or (STAT 150 and MATH 131 with a minimum grade of D-)

Course Fee

Differential Tuition Required

STAT 411 Fundamentals of Data Science

This course is an introduction to the elements of data science. Topics include data visualization, data wrangling, statistical learning and predictive analytics, text mining and spatial data.
3

Course Fee

Differential Tuition Required

STAT 422 Directed Studies

Individualized investigation under the direct supervision of a faculty member. (Minimum of 37.5 clock hours required per credit hour.)
1- 3

Special Notes

Maximum concurrent enrollment is two times.

Course Attribute

Variable Title Course

Repeatable Status

Course is repeatable with no limitations

Course Fee

Differential Tuition Required

STAT 489 Project in Data Science

This is a project course in data science and related fields. Interdisciplinary teams will analyze a new data science problem, develop a model, and control for error and overfitting.
2

Prerequisites

STAT 411 with a minimum grade of C

Mutually Exclusive Course

Credit allowed for only one of these courses: CS 489 and STAT 489

Course Fee

Differential Tuition Required