Course Title: Statistical Computing

Part A: Course Overview

Course Title: Statistical Computing

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH1275

Bundoora Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2006,
Sem 1 2007,
Sem 1 2008,
Sem 1 2009,
Sem 1 2010,
Sem 1 2011,
Sem 1 2012,
Sem 1 2013,
Sem 1 2014,
Sem 1 2015,
Sem 1 2016

MATH1275

Bundoora Campus

Undergraduate

171H School of Science

Face-to-Face

Sem 1 2018,
Sem 1 2019,
Sem 1 2020,
Sem 1 2021

MATH1276

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2006,
Sem 1 2007,
Sem 1 2008,
Sem 1 2009,
Sem 1 2010,
Sem 1 2011,
Sem 1 2012,
Sem 1 2013,
Sem 1 2014,
Sem 1 2015,
Sem 1 2016

MATH1276

City Campus

Undergraduate

171H School of Science

Face-to-Face

Sem 1 2017,
Sem 1 2018,
Sem 1 2019,
Sem 1 2020,
Sem 1 2021,
Sem 1 2022

Course Coordinator: Sevvandi Kandanaarachchi

Course Coordinator Phone: +61 3 9925 2880

Course Coordinator Email: sevvandi.kandanaarachchi@rmit.edu.au

Course Coordinator Location: 15.4.13

Course Coordinator Availability: Contact via email for appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

Assumed Knowledge

A pass in any VCE Year 12 mathematics course is desirable


Course Description

This course provides an introduction to the role of Statistics in the Data Analysis Process. The emphasis is on learning statistical methods for processing data to yield information that leads to informed decision-making in work and research contexts. The statistical package SPSS is used in the analysis of data.
Topics include the following: Types of variables; Sampling: probability and non-probability samples; Graphical methods for describing data; Numerical methods for describing data; Summarising bivariate data; Probability and Probability distributions; Normal distribution and its properties and hypothesis testing with the normal distribution.
 


Objectives/Learning Outcomes/Capability Development

 This course contributes to the program learning outcomes for the following program(s):

1.0 Critical Analysis and Problem Solving
1.1 Ability to apply scientific principles and methods to describe and analyse research data
1.2 Ability to know what questions to ask, who to ask and how to ask them.

2.0 Teamwork & Leadership
2.1 Ability to work in collaboration with others on data analysis tasks

3.0 Communication and Presentation
3.1 Ability to communicate in a range of forms (written, electronic, graphic, oral) and to tailor the style and means of communication to the circumstances of the situation and capabilities and sensitivities of the psychological disciplines.
3.2 Ability to constructively give and receive feedback

4.0 Self management
4.1 Ability to take personal responsibility for decisions and actions while being aware of limits of knowledge and skill and when to seek help. 

For more information on the program learning outcomes for your program, please see the program guide.  


On completion of the course, you will be able to:

  1. Apply a range of sampling techniques and be conversant with their strengths and weaknesses in data collection.
  2. Discuss the role of statistical methods in analysing data.
  3. Use SPSS to set up data files and use menu commands to analyse data.
  4. Construct appropriate graphical displays of data using SPSS.
  5. Numerically summarise data via SPSS using descriptive statistics.
  6. Describe the properties of the normal distribution and perform hypotheses testing.


Overview of Learning Activities

 

You will be actively engaged in a range of learning activities such as lectorials, tutorials, practicals, laboratories, seminars, project work, class discussion, individual and group activities. Delivery may be face to face, online or a mix of both. 

You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course


Overview of Learning Resources

 

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course

There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.


Overview of Assessment

Assessment Tasks

Assessment Task 1: Introductory Practical Assessments
Weighting: 30%
This assessment supports CLOs 1-6 

Assessment Task 2: Intermediate Practical Assessments
Weighting: 30%
This assessment supports CLOs 1-6 

Assessment Task 3: Collaborative Learning Component 
Weighting: 40%
This assessment supports CLOs 1-6 

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.