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
  1. Introduction to R and Quantitative Data Analysis

Delivered byDr 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.