Course Title: Professional Practice for Statisticians

Part A: Course Overview

Course Title: Professional Practice for Statisticians

Credit Points: 12.00


Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2135

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

 Sem 2 2006,
Sem 2 2007,
Sem 2 2008,
Sem 1 2009

Course Coordinator: Kaye Marion

Course Coordinator Phone: +61 3 99253162

Course Coordinator Email: k.marion@rmit.edu.au

Course Coordinator Location: 8.9.37


Pre-requisite Courses and Assumed Knowledge and Capabilities

None


Course Description

Professional practice for statisticians is a final semester course that aims to further prepare graduates to tackle open-ended problems. This course focuses on statistical modelling tasks commonly encountered by professional statisticians working with large data sets. In assisting you to deal with the large range of possible strategies and software packages that are, or can be, used in professional work settings the course will focus on helping you identify the principles for successfully manipulating (including transferring), analysing, interpreting and presenting data. In focussing on principles, the course is designed to help you develop appropriate strategies when unfamiliar tasks or software packages are encountered during your professional work.


Objectives/Learning Outcomes/Capability Development

In this course you will develop the ability to:

  • appreciate the complex, diverse and evolving social, political and cultural dimensions of practicing as a statistics professional in organisational and community settings.
  • apply knowledge and skills to characterise, analyse and solve a wide range of problems.
  • contribute to professional work settings through effective participation in teams and organisation of project tasks.
  • communicate both technical and non-technical material in a range of forms (written, oral, electronic, graphic,) and to tailor the style and means of communication to different audiences.
  • appreciate the ethical considerations that inform judgments and decisions in academic and professional settings.
  • locate and use data and information and evaluate its quality with respect to its authority and relevance.


After completing this course, you will be able to:

  • summarize, analyse & interpret computational procedures for inference from data sets using appropriate software packages.
  • explain/justify the importance and impact of graphical displays for data analysis and interpretation.
  • apply and interpret univariate, bivariate and multivariate statistical procedures.
  • work in groups effectively.
  • construct graphical displays of data.
  • critically evaluate spreadsheet and program layouts.
  • describe the relationships in the data using tables, plots and graphs.
  • demonstrate effective communication of statistical data.
  • reflect on the issues raised when communicating technical data to audiences eg novice, expert.
  • write a professional CV.
  • present well at interviews .
  • find research material.


Overview of Learning Activities

During this course, you will:

  • attend lectures where the underlying theory will be presented.
  • prepare a class presentation or poster.
  • search for job advertisements and write a professional CV.
  • engage in practice interviews.
  • practice presentations.
  • attend sessions run by library staff.


Overview of Learning Resources

The teaching staff will provide handouts for this course.


Overview of Assessment

You will be assessed on your ability to work in teams and present your project work as well as  your ability to prepare a CV and complete set assignments.