Research Skills

Seeking support for your research efforts? The Center for Graduate Life provides key resources to strengthen and develop your research skills. Check the Calendar for upcoming events.

Thomas L. Reynolds Graduate Student Research Award

Up to $1,500 for doctoral or master’s students to assist with costs often overlooked in other funding sources.  For more information on this and other funding alternatives, visit the Graduate School's Funding site.  To apply for a fellowship, please visit the NinerScholars portal

Graduate Dean's Distinguished Dissertation Award

Only the very best research dissertations are picked each year for the Graduate Dean's Distinguished Dissertation Award.  This award is presented by the Graduate School to recognize outstanding research and scholarship by a doctoral student at UNC Charlotte. Award recipients receive a cash prize and possible participation in the annual meeting of the Council of Graduate Schools.

Nominations for the 2019 Dean's Distinguished Dissertation Award will be accepted through May 24.  Instructions are available for download.

Outstanding Master's Thesis Award

The Master’s Thesis Award goes annually to a student nominated by faculty for the quality of their thesis work.  Award recipients receive a cash prize and possible participation in the annual meeting of the Conference of Southern Graduate Schools. 

CGL GRAD Courses
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GRAD 6302/8302 Responsible Conduct of Research (2 credits) 

Focuses on practical skills and critical thinking about the responsible conduct of research, highlighting the nine areas of instruction required by the National Institutes of Health (NIH) and National Science Foundation (NSF).  Features speakers with expertise in various areas of professionalism and research ethics. This course is required for all doctoral students. Graded on a Pass/Unsatisfactory basis. (Fall, Spring)

GRAD 6100 Quantitative Methods I: Basic Statistics and Probability (3 credits)

Covers basic statistics and probability theory and prepares you to take a more advanced course on linear regression. Learn SAS, STATA, and R during the semester by participating in modules offered by Project Mosaic. By the end of the semester, students should know the steps that need to be taken to clean data prior to advanced analysis, strategies for combining data, graphing and measures of central tendency and dispersion. Also covers sampling theory, inferential statistics, and sampling distributions.

GRAD 6103/8103 Advanced Quantitative Methods Time Series Analysis and Classificatory Methods (3 credits)

The purpose of this course is to introduce students to three methods for analyzing quantitative data used frequently in public policy research. These are two classificatory methods, factor analysis and cluster analysis, and an extensive overview of time series analysis. Students are required to be familiar with the principles of statistical analysis and, in particular, with regression analysis to take this course.