Quantitative Research Methods - Statistical Analysis and Data Modelling (via Zoom) - 12 October (Day 1)

Through a sequence of four learning modules, this course will enhance your skills in the analysis phase of the research lifecycle.  It begins with an introduction to the basics of statistical modelling using R, progressing to more complex concepts and models in later modules. Each module consists of interactive online tutorials plus a Zoom sessions in which the instructor facilitates discussions of the material contained in the tutorials. Students who register to participate in the Zoom session will be expected to actively participate in the discussions through group work or with the entire class.

This course is suitable for HDR students in the second or third stage of their candidature. It supports the students’ development in the Research Knowledge and Skills element of the MAPARC research student capability framework and the Research Lifecycle element of the UTS Research Outcomes Capability framework.

Time: 9:30 AM - 11:30 AM

Facilitator: A/Prof Tapan Rai

Day One: Monday, 12 October 2020

Introduction to statistical modelling: Simple and Multiple Linear Regression

This module begins with a quick conceptual review of simple linear regression which forms the basis for more advanced statistical modelling. You will also learn how to implement multiple regression models in R and be introduced to the use of residual plots is assessing model fit. Specifically, you will:

• Understand the concept of linear regression
• Run a multiple linear regression model in R
• Use a linear regression model to make predictions
• Use the output of a linear regression model to draw inferences
• Use residual plots to check model assumptions
• Understand the coding of categorical predictors in regression and related models

Zoom meeting link:
https://utsmeet.zoom.us/j/94928142604


Students need to complete the LinkedIn Learning course Learning R and to install R and RStudio
on their computer prior to participating in this short course. For free access to all LinkedIn Learning Courses (including Learning R), sign in to LinkedIn with your UTS email address.

FAQ'S

What if I can no longer attend, do I need to cancel?

Yes. Please contact the Researcher Development team at grs_rd@uts.edu.au for workshop cancellation.

If you fail to cancel your registration and are absent three or more times in a session, you will be suspended from the program for 1 year. You will be notified by email prior to your suspension being applied.

If a course is more than one day, am I required to attend all days?

We strongly recommend that you attend all days in a course in order to get the full learning experience that it has to offer. However, if you need to miss one of the days, please go through the material for that day on UTS Online before participating in the subsequent Zoom sessions for that course.

Also, If you are unable to attend one of the days, please contact us at grs_rd@uts.edu.au prior to the session, so that we can plan the best experience for the other students in the course.

Who should I contact if I have any further questions?

Please contact the Researcher Development team at grs_rd@uts.edu.au. Please note you must use your UTS student email address for official university correspondence