Overview
This course is designed to provide students with an understanding of regression modelling techniques, while allowing for hands-on coding examples in R or Stata.
Working with an example dataset, you will gain the necessary skills to manipulate variables, analyse relationships between variables, and interpret model outputs. The course will primarily focus on linear regression modelling and extend to multiple regression modelling, with brief overviews of other regression techniques.
Exercises will include:
- variable creation and recoding
- descriptive statistics
- regression analyses
- interpretation in Stata or R.
Who should attend
- Those with limited knowledge and experience with regression or other statistical modelling techniques who are seeking fundamental knowledge and skills of regression modelling
- Researchers, evaluators and PhD students
Entry requirements
You need to be familiar with basic statistics, including:
- understanding types of variables
- univariate descriptive analyses
- bivariate analyses such as chi-square, t-tests, ANOVA and correlations.
If you don’t already have this knowledge, please consider completing Social Research Methods 8 – Introduction to Quantitative Data Analysis for the fundamental knowledge before undertaking Regression Analysis.
What you'll learn
- Understand the basic principles and assumptions of regression modelling.
- Learn how to run and interpret simple linear regression analysis results.
- Extend the knowledge to multiple regression modelling to analyse the relationships among multiple predictors and a single outcome variable.
- Gain familiarity with other regression modelling techniques, such as logistic regression.
- Run statistical software outputs (Stata/R) to conduct regression analyses and interpret the output.
Time commitment
This is an online course that will require roughly 7 hours to complete.
- 2 half-days (9am to 12:30pm AEST)
Assessment
Certification and accreditation
Students who successfully complete the course will receive a Certificate of Completion to verify their skills and achievements.
Facilitators
Cost
| Applicant | Price |
|---|---|
| Standard rate | A$610 |
| Early bird (book 1 month before the course starts) | A$519 |
| Groups of 3 or more (per person) | A$488 |
| UQ students | A$427 |
| Other students | A$458 |
We're accepting expressions of interest for this course.
If sufficient numbers are reached, a date will be scheduled. Registrations will close 7 days before the course starts.
We offer discounts to not-for-profit employees and developing country participants. Contact us for details.
GST is included in the cost for participants in Australia. If you are participating from outside Australia, GST will be excluded
Discounts can't be used with other discounts, offers or special promotions.
If you’re participating outside Australia, contact us before you enrol to ensure Australian taxes are excluded from the cost.
Payment optionsWe accept credit cards (Visa/MasterCard) for payment, including corporate credit cards. We can also invoice corporate and government clients. If you want to discuss payment options, please contact our team at issr.education@uq.edu.au.
Related courses
This course is part of the Social Research Methods suite. There are 11 courses within this suite – see the other related courses below:
- Social Research Methods 1 – Gathering and Analysing Qualitative Data
- Social Research Methods 2 – Evaluating Social, Health and Human Service Programs
- Social Research Methods 3 – Social Cost-Benefit Analysis
- Social Research Methods 4 – Longitudinal Data Analysis
- Social Research Methods 5 – Data literacy, storytelling and influencing decision-makers
- Social Research Methods 6 – Survey Design
- Social Research Methods 7 – Principles of Research Design
- Social Research Methods 8 – Introduction to Quantitative Data Analysis
- Social Research Methods 10 – Data Wrangling with R: An Introduction
- Social Research Methods 11 – Factor Analysis
Contact
Institute for Social Science Research
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