This course aims to provide you with the understanding and experience to undertake a basic research project in the social or health sciences using Stata as the statistical tool.
Dr Joanna Dipnall is an applied statistician with interests in the advanced statistical methods, including machine learning and deep learning techniques. She completed her Honours in Econometrics with Monash University and her PhD with IMPACT SRC, School of Medicine, Deakin University. Joanna works extensively with registry and linked medical data and collaborates extensively with the Faculty of IT at Monash to supervise Masters and PhD students to integrate artificial intelligence within health research. Joanna teaches within the Monash Biostatistics Unit and is the Unit Co-coordinator for the Monash Masters of Health Data Analytics course. Joanna has taught advanced statistical methods for many years at universities and for ACSPRI.
Stata is a comprehensive integrated package for data management, analysis and graphics. Stata has a comprehensive GUI interface. Sample datasets will be provided, but you are encouraged to bring some of your own data for analysis in Excel or ASCII format. Teaching and practice will be closed integrated, and individual assistance will be provided as needed.
The course is suitable for beginners to the Stata package and will be presented in a way that introduces survey research. It is also appropriate to those familiar with Stata as it extends the capabilities of more experienced researchers.
Day 1
Introduction
- About Stata
- Inputting data into Stata
- Exploring data in Stata
- Basic data modifications in Stata
Day 2
Basic Analysis
- Tables and Correlations
- T-tests and analysis of variance
- Handling dates
- Introductrion to Stata graphics
Day 3
More Analysis
- Developing scales
- Factor analysis
- Merging datasets
- Advanced Stata graphic
Day 4
“Day of Regression”
- OLS Regression
- Logistic Regression
- Poisson Regression
- Stepwise Regression
Day 5
Survey Data
- Analysis of survey data in Stata
- Group reports using Stata, based on research hypothesis
This course may run in a computer lab, or you may be advised to bring your own laptop with specified software including Stata.
We will let you know in advance.
Notes and sample datasets will be provided, but you are encouraged to bring some of your own data for analysis in Excel or ASCII format.
This course assumes that participants have;
(1) reasonable understanding of statistics to be able to comprehend the material covered in the course outline above (e.g. regression analysis)
(2) some familiarity with a PC environment including keyboard skills and understanding of folder and file structures,
(3) some experience in using Microsoft Word and Excel or their equivalent
(4) some experience using a text editor such as Notepad, UltraEdit.
It does not assume prior experience with Stata, SAS, SPSS or any other specific statistical packages although any such experience would be helpful.
No specific references are suggested although participants are encouraged to bring any Stata documentation they may have. For an overview of the Stata package, please visit http://survey-design.com.au or http://stata.com.
Q: Do I have to have any prerequisites to do this course?
A: It would be advised that you have completed an introductory statisics course ie Fundamentals of Statsistics.
New skills learnt and covered a lot of material in 5 days. (Winter 2018)
Really enjoyed this class, a good mix of consolidating some basic concepts and applying stata commands. It was great to come away with files I can use as a template for my analyses. (Winter 2017)
This course improved my knowledge & skills in STATA. I did have very little knowledge on STATA, after this course I learned a lot. (Winter 2017)
Good balance of exercise, examples and own work. (Spring 2016)
Gave me the technical skills to use STATA (Summer 2016)
Very helpful practical course, intense but highly recommended. (Summer 2015)
Jo ran an excellent and energetic course both hands on and explained complicated concepts simply. Love the hands on. (Winter 2014)
Highly relevant to my work & research. Would highly recommend to others. (Winter 2014)
The instructor's bound, book length course notes will serve as the course texts.