Competencies and Learning Objectives for Biostatistics
| Number | Competency | Specific course(s) that allow assessment |
|---|---|---|
| 1 | Apply the theoretical foundations of probability theory and distribution theory | BIOSTAT601 |
| 2 | Apply foundational mathematical statistical concepts and skills for conducting statistical inference | BIOSTAT602 |
| 3 | Perform linear regression model fitting and diagnostic assessment | BIOSTAT650 |
| 4 | Understand the main components of generalized linear models and how to choose an appropriate model based on the outcomes and study design | BIOSTAT651 |
| 5 | Fit generalized linear models for various outcome types and provide correct interpretation of the results | BIOSTAT651 |
| 6 | Use general linear models and linear mixed models for analyzing correlated continuous data, as well as marginal (i.e. generalized estimating equations), conditional (i.e. generalized linear mixed model) and transition models for analyzing correlated discrete data | BIOSTAT653 |
| 7 | Properly interpret and present the results from such longitudinal analysis to both methods and substantive audiences | BIOSTAT653 |
| 8 | Analyze, interpret, and communicate through written and oral presentation the results of a statistical analysis of biomedical data to an audience from a variety of health-related areas (e.g. public health, medicine, genetics, biology, psychology, nursing, or pharmacy) and for the broad scientific community | BIOSTAT699 |
| Number | Competency | Specific course(s) that allow assessment |
|---|---|---|
| 1 | Apply the theoretical foundations of probability theory and distribution theory* (same as MS in Biostatistics) | BIOSTAT601 |
| 2 | Apply foundational mathematical statistical concepts and skills for conducting statistical inference* (same as MS in Biostatistics) | BIOSTAT602 |
| 3 | Perform linear regression model fitting and diagnostic assessment* (same as MS in Biostatistics) | BIOSTAT650 |
| 4 | Understand the main components of generalized linear models and how to choose an appropriate model based on the outcomes and study design* (same as MS in Biostatistics) | BIOSTAT651 |
| 5 | Fit generalized linear models for various outcome types and provide correct interpretation of the results* (same as MS in Biostatistics) | BIOSTAT651 |
| 6 | Apply data science techniques in the analysis of health data, including data cleaning, exploratory data analysis, and data visualization | BIOSTAT620 |
| 7 | Apply basic informatics and computational techniques in the analysis of big health data, and interpret results of statistical analysis | BIOSTAT625 |
| 8 | Master the theoretical foundations to design and apply machine learning algorithms in biomedical applications. Understand the process of developing and assessing machine learning algorithms, including design principles, parameter estimations, and performance evaluation. Understand a diverse set of commonly used machine learning algorithms in both supervised and unsupervised learning scenarios | BIOSTAT626 |
| 9 | Apply quantitative techniques commonly used to summarize and display big public health data | BIOSTAT629 |
| 10 | Apply descriptive and inferential methodologies according to the type of study design or sampling technique for answering a particular public health question | BIOSTAT629 |
| Number | Competency | Specific course(s) that allow assessment |
|---|---|---|
| 1 | Master the theoretical foundations of probability theory and apply the theoretical principles in probabilistic modeling. | BIOSTAT680 |
| 2 | Apply the advanced probability theory and distribution theory | BIOSTAT801 |
| 3 | Derive the advanced theoretical mathematics of statistical inferences | BIOSTAT802 |
| 4 | Understand and apply ethical principles and professional norms to scientific research, covering 10 core areas: data management, mentor/mentee roles, publication, peer review, collaboration, research misconduct, human subjects, animal welfare, conflict of interest, and societal impacts. | BIOSTAT810 |
| 5 | Develop new statistical methodology for application in real life problems in Biosciences | Dissertation |
| 6 | Prepare a methodological manuscript for publication in a peer-reviewed biostatistical journal | Dissertation |