Odum Institute

This course introduces students to Stata and data management. It is tailored for beginners and researchers who want to learn how to manage data more effectively. Each day, the class will demonstrate how to use the commands, followed by hands-on exercises using sample datasets. This class will cover 3 afternoons (9/26, 9/28 and 9/30). Learn more and register.

Integrated mixed methods are used to answer questions that necessitate more than one method to achieve a holistic understanding. Combining qualitative and quantitative approaches can enhance conversations about theory, practice, and/or policy. This demanding paradigm requires knowledge, skill, and expertise in quantitative and qualitative methods, as well as the art of intentionally integrating the approaches to and findings from each mode of inquiry. This class will take course over 3 mornings (9/26, 9/28 and 9/30). Learn more and register.

This course introduces students to Stata and data management. It is tailored for beginners and researchers who want to learn how to manage data more effectively. Each day, the class will demonstrate how to use the commands, followed by hands-on exercises using sample datasets. This class will cover 3 afternoons (9/26, 9/28 and 9/30). Learn more and register.

This 4-day, 2-part short course will provide an overview of statistical machine learning and data mining techniques with applications to the analysis of real data. Supervised learning techniques will be covered, including penalized regression such as LASSO and its variants, support vector machines. The main emphasis will be on the analysis of real data sets from various scientific fields. The techniques discussed will be demonstrated in R. PLEASE NOTE: This course will be divided in to two parts: September 20…

This 4-day, 2-part short course will provide an overview of statistical machine learning and data mining techniques with applications to the analysis of real data. Supervised learning techniques will be covered, including penalized regression such as LASSO and its variants, support vector machines. The main emphasis will be on the analysis of real data sets from various scientific fields. The techniques discussed will be demonstrated in R. PLEASE NOTE: This course will be divided in to two parts: September 20…

This workshop will introduce the advanced data visualization capabilities in R and to the concepts of the grammar of graphics. We will demonstrate how to access ggplot2 using a graphical user interface library in R as well as an R shiny app. These environments provide the user a “point and click” interface for accessing the power of ggplot2 and can generate R syntax automatically thereby providing users a boost up the learning curve for understanding the grammar of graphics used…

This course will provide an introduction to descriptive and inferential network analysis. In the morning we will cover descriptive network analysis. We will cover both empirical analysis and network simulation using statistical network models. Real-world network data and R code will be presented through interactive workshop sessions in both the morning and afternoon. There are no formal prerequisites for the course, but a background in basic statistical analysis (ie: regression) will be useful. Learn more and register.

This course will provide an introduction to effectively designing web surveys to avoid common pitfalls that impact data quality and introduce measurement error. The course will focus on the following elements of web survey design. Special considerations for designing web surveys to accommodate mobile response will also be covered. This course will also provide an overview of the various web survey software systems available and offer practical guidance on selecting appropriate platforms. Learn more and register.

This course will focus on both qualitative and quantitative data collection techniques to measure health. Participants will be able to describe and recognize the characteristics, advantages and disadvantages and practical consequences of quantitative and qualitative data collection methods in a health research setting; set out quality criteria for assessing qualitative research and discuss these criteria with regard to their own research; apply the basis of the thematic analysis to own data. Learn more and register.

Daily life methods are a family of methods used to study what people do in their ordinary environments in their everyday lives through collecting data at least once a day for several days. Two common forms of daily life methods, daily diaries and experience sampling methods, will be emphasized in this course. This course will be interactive and present opportunities for attendees to start thinking about how to apply daily life methods to their own programs of research. Learn more…