Applied Statistics Graduate Certificate
Graduate School Policies and Procedures apply to this program.
Please click here to see Mathematical and Statistical Sciences department information.
Introduction
Coordinator: Joshua French Ph.D.
Telephone: 303-315-1709
E-mail: Joshua.French@ucdenver.edu
Website: https://clas.ucdenver.edu/mathematical-and-statistical-sciences/graduate-certificate-applied-statistics
There is a growing need for qualified statistical analysts of the ever-increasing amounts of data collected in business, industry, and government. The Certificate in Applied Statistics program is designed to give students a strong background in statistical methodology and data analysis in preparation for opportunities in the workforce or for graduate studies.
Students will gain competence in such topics as descriptive statistics, estimation, confidence intervals, probability and inferential techniques, simple and multiple regression, analysis of variance, and more advanced topics. Students can focus on a particular application area such as economics, psychology, sociology, geology, or environmental science through the choice of an elective course and the data analysis project.
These degree requirements are subject to periodic revision by the academic department, and the College of Liberal Arts and Sciences reserves the right to make exceptions and substitutions as judged necessary in individual cases. Therefore, the College strongly urges students to consult regularly with their Applied Statistics faculty advisor to confirm the best plans of study before finalizing them.
Certificate Requirements
Students must maintain a 3.0 GPA or above in these courses with no credit given for courses with grades below B-. Since a certificate is a University of Colorado Denver certification of a student's specialized knowledge in an advanced subject area, all courses in the certificate program must be taken in residency at University of Colorado Denver. Students much be enrolled in one course per year to maintain their status in the certificate program.
Certificates must be completed within three years from matriculation.
- Students must complete a minimum of 12 MATH credit hours.
- Students must complete a minimum of 12 graduate (5000-level or higher) credit hours.
- Students must earn a minimum grade of B- (2.7) in all courses taken at CU Denver and must achieve a minimum cumulative certificate GPA of 3.0. All graded attempts in required and elective courses are calculated in the program GPA. Students cannot complete program or ancillary course requirements as pass/fail.
- Students must complete all coursework with CU Denver faculty.
Four courses are required as detailed below.
Fundamental Courses
Code | Title | Hours |
---|---|---|
Complete the following courses: | 6 | |
Statistical Inference (Offered: Spring) | ||
Applied Regression Analysis (Offered: Fall, Spring, Summer) |
Advanced Applications
Code | Title | Hours |
---|---|---|
Complete one of the following courses: | 3 | |
Topics vary from year to year. Course must be pre-approved by certificate coordinator and cannot be MATH 5830. Representative courses include: | ||
Intro to Statistical and Machine Learning | ||
Machine Learning Methods | ||
Experimental Designs | ||
Stochastic Processes | ||
Spatial Data Analysis | ||
Statistical and Machine Learning | ||
Bayesian Statistics | ||
Topics in Probability and Statistics | ||
Any additional MATH course pre-approved by the Director of Statistical Programs |
Elective
Code | Title | Hours |
---|---|---|
Complete one of the following courses: | 3 | |
Any statistics course in the Department of Mathematical and Statistical Sciences at the 5000 level or higher (must be pre-approved by the Certificate Coordinator). MATH 5830 cannot apply towards the certificate. | ||
Economic Forecasting | ||
Econometrics I | ||
Econometrics II | ||
Applied Statistics for the Natural Sciences | ||
Seminar: Quantitative Data Analysis | ||
An equivalent course pre-approved by the Director of Statistical Programs |
To learn more about the Student Learning Outcomes for this program, please visit our website.