2021 CARMA Short Courses
Event details
08 November - 18 November 2021
UniSA Business is pleased to host short courses offered by the Consortium for the Advancement of Research Methods and Analysis (CARMA). Two courses are offered in November 2021 and the instructors are international experts in research methodology.
This is a great opportunity to practice and develop your skills in research methods and meet some of the greatest names in the field. Don’t miss the chance to learn best practice from our international experts!
| Week | Dates (8:30 am - 1:30 pm) |
Course | Instructor |
| 8 - 11 November | Monday - Thursday | Introduction to R and Quantititative Data Analysis | Dr Ron Landis |
| 15 - 18 November | Monday - Thursday |
Introduction to Python for Quantitative and Qualitative Research |
Dr Jason Kiley |
- Introduction to R and Quantitative Data Analysis
Delivered by: Dr Ronald S Landis, Illinois Institute of Technology, USA
Dr Ron Landis is the Nambury S. Raju Professor of Psychology. He currently serves as Associate Editor for the Journal of Business and Psychology and is on the editorial boards of Personnel Psychology, Organizational Research Methods, Journal of Management, Human Performance and Journal of Applied Psychology**
Method Focus: Quantitative
What will Be Covered: Data management and fundamental statistical analyses (descriptive, correlation, regression, t-test, ANOVA) in R.
Who will Benefit: Junior HDR students and/or researchers new to quantitative analysis in R.
Required Software: R (download here), R Studio (download here)
2. Intermediate SEM, Model Evaluation
Delivered by: Dr Jason T Kiley, Oklahoma State University, USA
Method Focus: Mixed (both quantitative and qualitative)
What will Be Covered: we will cover collecting data at scale using several techniques, including programmatic interfaces for obtaining data from WRDS, application programming interfaces (APIs) for a wide range of academic and popular data (e.g., The New York Times), web scraping for quantitative and text data, and computer-assisted manual data collections.
Who will Be Benefited: Researchers are interested in collected and analysing data from open (e.g., Tweeters) or existing data sources.
