Available in 2021
Course code



10 units


1000 level

Course handbook


Extracting and communicating information from data lies at the heart of statistics and data science. In practice, data is not often in an immediately useable format, requiring management, manipulation and error-checking. Visualisation of data is an invaluable asset in finding and communicating key information as well as in error-checking. By the end of this course students will be able to effectively work with introductory methods for data wrangling and visualisation of data while developing coding skills using the Python language which is one of the most popular and preferred languages used in practice. No prior programming experience is necessary.

Interested in studying further statistics courses to develop your skills and improve your employability? Information about available statistics courses can be found here: https://www.newcastle.edu.au/school/mathematical-and-physical-sciences/study/statistics-courses

Availability2021 Course Timetables


  • Semester 1 - 2021

Learning outcomes

On successful completion of the course students will be able to:

1. Implement data checking, wrangling, tidying, and basic management methods.

2. Apply exploratory techniques to identify and describe underlying patterns in data.

3. Identify and avoid common flaws in the presentation of data.

4. Communicate and report upon data effectively.

5. Analyse, visualise, and report on data using the Python programming language.


  • Processes for data checking
  • Dealing with errors
  • Understanding types of data
  • Exploratory data techniques
  • Presenting data using Python data analysis libraries
  • Visualisation using Python data visualisation libraries

Assessment items

Quiz: Online Quizzes

Written Assignment: Written Assignment 1

Written Assignment: Written Assignment 2

Formal Examination: Formal exam

Compulsory Requirements

In order to pass this course, each student must complete ALL of the following compulsory requirements:

General Course Requirements:

  • Computer Lab: There is a compulsory attendance requirement in this course. - Students must attend a minimum of 80% of computer labs.

Contact hours


Computer Lab

Face to Face On Campus 2 hour(s) per Week for Full Term


Face to Face On Campus 1 hour(s) per Week for Full Term

The University of Newcastle acknowledges the traditional custodians of the lands within our footprint areas: Awabakal, Darkinjung, Biripai, Worimi, Wonnarua, and Eora Nations. We also pay respect to the wisdom of our Elders past and present.