Introduction to Stata

The Introduction to Stata short course provides an introduction to the statistical analysis software program Stata (Release 15), covering basic data management issues and popular epidemiological analyses.

The course involves students using Stata by following a detailed course manual with support from statisticians who are experienced Stata users.

Course outline

The course is self-paced and will cover the following topics:

  • Entering data
  • Using commands on menus
  • Data labelling
  • Descriptive statistics
  • Epidemiological data analysis including logistic regression
  • Do-files and log-files

Further information

Please note: Participants must bring a laptop to this course

Registration for the course begins at:
9:30am - for participants that require Stata to be installed
9:45am - for participants that already have Stata installed

The course is self-paced, with an estimated finish time of 5:00pm

Who should attend

This introduction is suitable for those who have never used a computer to perform statistical analysis, but who have a basic understanding of statistical concepts such as histograms, t-tests, linear regression and odds ratios.

SPHPM Doctoral Candidates – please email to register

Course Directors

Dr Joanna Dipnall


Joanna Dipnall is an applied statistician with particular interests in the areas of data mining and machine learning. She completed her Honours in Econometrics with Monash University and PhD with IMPACT SRC, School of Medicine, Deakin University where she blended machine learning with traditional statistical techniques to develop Risk Index for Depression (RID). She has worked externally in the commercial world as an applied researcher and statistical consultant throughout her career and taught advanced statistical methods using the Stata statistical software for many years privately and with ACSPRI and NZSSN.

Prof Rory Wolfe


Prof Rory Wolfe has been a biostatistician at DEPM since 2000 and contributes to a wide range of epidemiological, public health and clinical research studies. He also leads research on aspects of statistical methodology as applied to health research.

Rory obtained his PhD in applied statistics from Southampton University (UK) and subsequently did postdoctoral research in statistical methodology for longitudinal studies. He is a member of the Statistical Society of Australia and the Royal Statistical Society (UK). He is involved in the delivery of postgraduate coursework for the Biostatistics Collaboration of Australia.

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