STAT1100
10 units
1000 level
Course handbook
Description
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
Availability2024 Course Timetables
Callaghan
- Semester 1 - 2024
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.
6. Recognize how data wrangling is implemented in real-life applications
Content
- Presentation and interpretation of data
- Processes for data checking, cleaning, filtering, and dealing with errors
- Understanding types of data
- Exploratory data techniques
- Introduction to data modelling and analysis
- Presenting data using Python data analysis libraries
- Visualisation using Python data visualisation libraries
- Applications of data wrangling in science and industry
Assessment items
Quiz: Online Quizzes
Written Assignment: Written Assignment 1
Written Assignment: Written Assignment 2
Formal Examination: Formal exam
Contact hours
Semester 1 - 2024 - Callaghan
Computer Lab-1
- Face to Face On Campus 2 hour(s) per week(s) for 13 week(s) starting in week 1
- Compulsory Requirement: Students must attend 80% of sessions.
Lecture-1
- Face to Face On Campus 2 hour(s) per week(s) for 13 week(s) starting in week 1
Course outline
- STAT1100 - Semester 1, 2024 (Callaghan) (PDF, 188.3 KB)
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.