Statistics opens the door to understanding our world through the exploration of data and the modelling of uncertainty. The need for statistics is growing rapidly as our ability to collect massive amounts of data outruns our ability to understand and use the data we collect. Hal Varian, Chief Economist at Google, declared that “the sexy job in the next ten years will be statisticians”, as the challenge of understanding large, complex data structures mounts. It is estimated that 2.5 exabytes of data is generated every single day, with the accumulated amount of data doubling every 18 months, and that 90% of all data ever gathered was produced within the last two years. What’s more, statistics is critical for every discipline for which data play a role, and in responding to the world’s biggest challenges such as climate change, terrorism, health and medicine, and global economic conditions. Some of the world’s largest employers of statisticians include Google and Facebook as well as governments, financial institutions, medical and pharmaceutical industries, universities and many other sectors. By completing a BStat at ANU, you stand ready to meet humanity’s biggest challenges by understanding the world we observe through the eyes of data and statistical and probability modelling.

The Bachelor of Statistics is designed to produce graduates who are able to deliver crucial insight within an increasingly information driven business environment. Examples of employment opportunities include:

• Applied research, for example market research
• Academic research, particularly social sciences
• The Government sector employs statisticians to assist with policy/program development and evaluation
• Business analyst within finance and banking sector

Learning Outcomes

1. Review and synthesise a broad range of statistical knowledge from their chosen major
2. Use the R statistical computing language to carry out a wide variety of statistical tasks
3. Carry out model selection in a multiple linear regression modelling context
4. Describe the concepts of stochastic processes in discrete and continuous time
5. Describe and interpret probability theory, continuous random variables, and sampling distributions and the central limit theorem
6. Analyse programming problems to suggest, design and implement appropriate modular program structures, based on a data-directed approach.