Course Title: Mathematics and Statistics

Part A: Course Overview

Course Title: Mathematics and Statistics

Credit Points: 12.00


Course Code




Learning Mode

Teaching Period(s)


City Campus


145H Mathematical & Geospatial Sciences


Sem 1 2006,
Sem 2 2006,
Sem 1 2007,
Sem 2 2007,
Sem 1 2008,
Sem 2 2008,
Sem 1 2009,
Sem 2 2009,
Sem 1 2010,
Sem 2 2010,
Sem 1 2011,
Sem 2 2011,
Sem 1 2012,
Sem 2 2012,
Sem 1 2013,
Sem 2 2013,
Sem 1 2014,
Sem 2 2014,
Sem 1 2015,
Sem 2 2015,
Sem 1 2016,
Sem 2 2016


City Campus


171H School of Science


Sem 1 2017,
Sem 2 2017,
Sem 1 2018,
Sem 2 2018,
Sem 1 2019,
Sem 2 2019,
Sem 1 2020

Course Coordinator: Miss Delaram Pahlevani

Course Coordinator Phone: N/A

Course Coordinator Email:

Course Coordinator Availability: By appointment

Pre-requisite Courses and Assumed Knowledge and Capabilities

VCE Further Mathematics (or equivalent)

Course Description

MATH 2123 - Mathematics and Statistics will introduce you to a number of mathematical and statistical procedures often used in science. The course aims to provide the theoretical foundations that any scientist will require to meet community and regulatory requirements. The learning of statistics will integrate theory and applications using a problem-based approach aided by the use of the Minitab statistical package. The course will focus on developing your abilities in critical analysis and decision making as well as teamwork and reflection.

Objectives/Learning Outcomes/Capability Development

On successful completion of this course you will be able to

  1. perform appropriate graphical displays of data and understand the role of such displays in data analysis;
  2. calculate probabilities of binomial and normal distributions;
  3. construct point and interval estimation for a mean and a proportion;
  4. conduct hypothesis tests for a mean and a proportion, and compare two-sample means and proportions;
  5. carry out linear regression analyses;
  6. use a statistical package to carry out descriptive and simple inferential statistical analyses.


Overview of Learning Activities

You will be expected to attend lectures, computer laboratories and practical tutorial sessions. The lecture, laboratory and practical tutorial classes will focus on problem-based activities encountered in science disciplines. These problems will be used to assist you to construct appropriate graphical displays of data, understand the nature of random variables through direct calculation and computer simulation, perform quality assessment tasks using software packages and understand the calculations involved in such tasks and to be aware of assumptions that are necessary for the validation of results.   The instructor will use demonstrations to provide you with an insight into the mental processes one goes through when mapping real life problems to abstract mathematical and statistical procedures and then to pen-and-paper calculations or the use of Minitab. The instructor will demonstrate the problem identification-solution process by “thinking aloud”. From this, you will be able to compare your own problem solving approaches to these problems. The instructor will use a mixture of such strategies as well as other means to highlight the main solution techniques and to show how the solution relates to the original model or data.   Each class will provide opportunities for you to receive feedback while attempting to determine solutions using pen-and-paper and suitable statistical packages. This is critical, as these skills will impact on the other mathematical knowledge and skills developed throughout the program. This will be achieved through problem solving during the lectures, laboratory sessions and in the practical tutorials. You are encouraged to find support from peers, tutors and the instructor when appropriate. 


Total study hours

Learner Directed Hours: 60
Teacher Guided Hours: 48


Overview of Learning Resources

You will be able to access course information and learning materials through the course Canvas page.  Lists of relevant reference texts and resources in the library will be provided. You will also use computer software available at the university computer laboratories and also available online through RMIT myDesktop.

Overview of Assessment


This course has no hurdle requirements


Assessment tasks


Assessment Task 1: Practical Tutorial Quizzes

Weighting 17.5%

This assessment task supports CLOs 1, 2, 3, 4 & 5

Assessment Task 2: Lab Tasks

Weighting 17.5%

This assessment task supports CLOs 1, 2, 3, 4, 5 & 6

Assessment Task 3: Mid-Semester Test

Weighting 15%

This assessment task supports CLOs 1, 2, 3, 4 & 5

Assessment 4: Examination

Weighting 50% 

This assessment supports CLOs 1, 2, 3, 4 & 5.