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.
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.
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.
STAT 150: with minimum grade of C
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.
May concurrently take MATH 132: with minimum grade of C
Topics in multiple linear regression, estimation of model parameters, inferences, diagnostics, model assumptions, ANOVA formulation.
MATH 350: with minimum grade of D- and STAT 355: with minimum grade of D- and (MATH 131: with minimum grade of D- or STAT 150: with minimum grade of D-)
Introduction to elementary sampling concepts. Includes random sampling, stratified sampling, cluster sampling and systematic sampling. Inferences and assumptions are presented for all sampling methods.
MATH 350: with minimum grade of D- and STAT 355: with minimum grade of D- and (MATH 131: with minimum grade of D- or STAT 150: with minimum grade of D-)
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.
Individualized investigation under the direct supervision of a faculty member. (Minimum of 37.5 clock hours required per credit hour.)