Students

STAT670 – Introductory Statistics

2015 – S1 External

General Information

Download as PDF
Unit convenor and teaching staff Unit convenor and teaching staff Other Staff
Petra Graham
Contact via petra.graham@mq.edu.au
E4A 543
TBD
Unit Convenor
Anne Karpin
Contact via anne.karpin@mq.edu.au
E4A 539
TBD
Credit points Credit points
4
Prerequisites Prerequisites
Admission to MAppStat or GradDipAppStat or MBiotech or MRadiopharmSc
Corequisites Corequisites
Co-badged status Co-badged status
STAT170
Unit description Unit description
This unit provides a broad introduction to statistical concepts and data analysis techniques, providing basic statistical knowledge. The unit is concerned with the development of an understanding of statistical practice and is illustrated by a study of those techniques most commonly used in the sciences, social sciences and humanities. The aim of statistical practice is to make the scientific research process efficient; for this reason statistics is used in disciplines ranging from accountancy to zoology. Topics covered in this unit include: data collection methods; data quality; data summarisation; and statistical models like the normal distribution, followed by sampling distributions and statistical inferences about means, proportions and quantiles. Also studied are methods of analysis relating to comparisons, counted data and relationships, including regression and correlation. Statistical computer packages are used for handling and analysing data along with word processing for reporting the results. However, no prior computing knowledge is assumed.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • Manipulate, classify and summarise different types of data both graphically and numerically.
  • Deeply understand and apply appropriate statistical techniques for analysis of various types of data.
  • Use Minitab to organise, manipulate, summarise and analyse data.
  • Be able to check the assumptions underlying the statistical models; carry out a statistical analysis and draw conclusions from the results of data analysis.
  • Interpret statistical results and write a statistics report based on the results of a statistical analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.
  • Have a deep understanding of the differences between one-sample and two-sample statistical tests and be able to apply the tests in statistical analysis.

Assessment Tasks

Name Weighting Due
Assignment 1 10% Wednesday Week 6 by 5pm
Assignment 2 10% Wednesday Week 11 by 5pm
Class Test 10% Tutorial class Week 8
Statistics Report 20% Wednesday Week 12 by 5pm
Final Examination 50% University Examination Period

Assignment 1

Due: Wednesday Week 6 by 5pm
Weighting: 10%

Assignment 1 provides students with an opportunity to develop and to apply sound statistical practice. This assessment task reinforces the concepts covered in lectures and the skills learned from the practical material. The assignment will be made available on iLearn two weeks prior to the due date. Submission is to be made through the iLearn turnitin link before the due date and time, more details will be made available in the assignment. Penalties apply for late submissions. Assignments submitted on Wednesday after the deadline incur a 5 mark penalty. Assignments submitted on Thursday incur a 10 mark penalty. Assignments submitted after Thursday will be awarded a mark of 0. Extensions will only be granted for cases in which an application for disruption to studies has been approved. 


On successful completion you will be able to:
  • Manipulate, classify and summarise different types of data both graphically and numerically.
  • Deeply understand and apply appropriate statistical techniques for analysis of various types of data.
  • Use Minitab to organise, manipulate, summarise and analyse data.
  • Be able to check the assumptions underlying the statistical models; carry out a statistical analysis and draw conclusions from the results of data analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.

Assignment 2

Due: Wednesday Week 11 by 5pm
Weighting: 10%

Assignment 2 provides students with an opportunity to develop and to apply sound statistical practice. It reinforces the concepts covered in lectures and the skills learned from the practical material. This assignment requires students to use Minitab to analyse data using appropriate techniques and part of the assignment must be submitted in the form of a statistical report. The assignment will be made available on iLearn two weeks prior to the due date. Submission must be via the iLearn turnitin link only and details will be given in the assignment. Penalties apply for late submissions and are as for Assignment 1. Extensions will only be granted for cases in which an application for disruption to studies has been approved. 


On successful completion you will be able to:
  • Manipulate, classify and summarise different types of data both graphically and numerically.
  • Deeply understand and apply appropriate statistical techniques for analysis of various types of data.
  • Use Minitab to organise, manipulate, summarise and analyse data.
  • Be able to check the assumptions underlying the statistical models; carry out a statistical analysis and draw conclusions from the results of data analysis.
  • Interpret statistical results and write a statistics report based on the results of a statistical analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.
  • Have a deep understanding of the differences between one-sample and two-sample statistical tests and be able to apply the tests in statistical analysis.

Class Test

Due: Tutorial class Week 8
Weighting: 10%

The Class Test will be held in week 8. Students within the greater Sydney area are required to come to the University during week 8 to sit the test. The convenor should be contacted before week 7 to organise when and where to go to sit for the test. Students beyond this area should contad the convenor regarding alternative arrangements. A page of formulae and relevant statistical tables will be provided in the class test. A statistics calculator may used in the class test. No other material (apart from writing equipment) will be permitted in the class test. Extensions will not be granted except for cases in which an application for special consideration is made and approved.  A supplementary class test will be given for students with an approved disruption to studies application.


On successful completion you will be able to:
  • Deeply understand and apply appropriate statistical techniques for analysis of various types of data.
  • Be able to check the assumptions underlying the statistical models; carry out a statistical analysis and draw conclusions from the results of data analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.
  • Have a deep understanding of the differences between one-sample and two-sample statistical tests and be able to apply the tests in statistical analysis.

Statistics Report

Due: Wednesday Week 12 by 5pm
Weighting: 20%

Students will be required to conduct statistical data analysis identifying and applying appropriate methods and techniques, interpret statistical results and summarise the results in a report. This assignment requires students to use Minitab to analyse data using appropriate techniques The requirements for the report will be made available on iLearn two weeks prior to the due date. Submission must be via the iLearn turnitin link only and details will be given in the requirements for the report. Penalties apply for late submissions and are as for Assignment 2. Extensions will only be granted for cases in which an application for disruption to studies has been approved. 


On successful completion you will be able to:
  • Have a deep understanding of the differences between one-sample and two-sample statistical tests and be able to apply the tests in statistical analysis.

Final Examination

Due: University Examination Period
Weighting: 50%

The Final Examination will be a three hour written exam (plus ten minutes reading time) and will be held during the examination period which runs from the 9th June to 26th June 2015. A page of formulae and relevant statistical tables will be attached to the final examination. Students will be permitted to take one A4 sheet (any colour), handwritten on both sides (using pens and/or pencils) into the final examination. This sheet must be submitted with your final exam paper at the conclusion of the exam. A statistics calculator may also be taken into the final examination. See the week 13 iLearn important information for more details on preparing for the final exam. 

The University Examination timetable will be available in draft form approximately eight weeks before the commencement of the examinations and in final form approximately four weeks before the commencement of the examinations at:http://www.timetables.mq.edu.au/

Students are advised that it is Macquarie University policy not to set early examinations for individuals or groups of students. All students are expected to ensure that they are available until the end of the teaching semester, i.e. the final day of the official examination period.

The only excuse for not sitting an examination at the designated time is because of documented illness or unavoidable disruption. In these special circumstances you may apply for Disruption to Studies via ask.mq.edu.auA supplementary examination will only be granted if the student has been found to have had a significant disruption to studies. If a supplementary examination is granted as a result of the disruption to studies process, the examination will be scheduled approximately two weeks after the conclusion of the official examination period.

Note that there is a University policy regarding requests for special consideration for examinations and the granting of supplementary examinations, which can be found at: http://students.mq.edu.au/student_admin/exams/disruption_to_studies/.

Students can submit disruption to studies request(s) through the following link: https://ask.mq.edu.au/

Grading in this Unit

The final Standardised Numerical Grade (SNG) in STAT670 will be based on students’ work during the semester and in the Final Examination. The determination of the final SNG will be based on performance of individual assessment tasks against criteria and standards as detailed in the Grading Policy (see http://mq.edu.au/policy/docs/grading/policy.html). Final grades will be awarded on the basis of students’ overall performance and the extent to which they demonstrate fulfillment of the learning outcomes listed for this unit.

 

Please note that students must perform satisfactorily in the Final Exam as well as the coursework in order to pass the unit.


On successful completion you will be able to:
  • Deeply understand and apply appropriate statistical techniques for analysis of various types of data.
  • Be able to check the assumptions underlying the statistical models; carry out a statistical analysis and draw conclusions from the results of data analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.
  • Have a deep understanding of the differences between one-sample and two-sample statistical tests and be able to apply the tests in statistical analysis.

Delivery and Resources

Classes

External students need to ensure that they keep pace with the internal class. Thy need to:

  • listen weekly to each 1 x 2 hour recorded Echo lecture beginning in Week 1
  • do the 1 x 1 hour compulsory tutorial beginning in Week 2
  • do the 1 x 1 hour compulsory practical beginning in Week 2

It is expected that external students participate in online discussion regarding the material covered each week.

Just as for the internal students, external students are expected to do 4 hours orf set activities per week as well as approximately 5 hour per week of additional study.

External students are strongly encouraged to consider whether this enrolllment option is suitable to them and to alternatively consider enrollment in the internal session. The timetable for classes can be found on the University web site at: http://www.timetables.mq.edu.au

Taking this unit exernally requires careful time management.

Required and Recommended Texts and/or Materials

  • A calculator with statistics mode is essential and should be brought to all classes.
  • For students with PC's the statistical software package Minitab 17 can be downloaded from: http://students.mq.edu.au/home/ (click on Software Downloads). For students with Mac computers iLab will be needed to be able to access Minitab. Please see iLearn for details. 

Recommended textbook used in this unit:

  • Modern Statistics: An introduction, Don McNeil and Jenny Middledorp (ISBN 9781486007011). This can be purchased in hard copy from, for example, the Coop Bookshop or in e-format (ISBN 9781486022120, access details to be provided in class).

Other recommended reading:

  • Introduction to the Practice of Statistics, Moore, D.S. and McCabe, G. P (W.H. Freeman)
  • Statistics without Tears by Rowntree (Penguin)
  • Mind on Statistics by Utts & Heckard (Thomson, 2004)
  • Elementary Statistics by Johnson & Kuby (Thomson, 2007)
  • Statistics: The Art & Science of Learning from Data by Agresti & Franklin (Prentice Hall, 2007)
  • The Statistical Sleuth by Ramsey and Schafer (Duxbury, 2002)

Technology Used and Required

Unit Web Page

Information relating to Stat670 can be found by visiting the Macquarie University Statistics Department web site. The URL for this site is: http://www.stat.mq.edu.au/

iLearn (which is a version of Moodle) is used for delivery of STAT670 course material and can be accessed at: http://ilearn.mq.edu.au

Unit Schedule

WEEK

LECTURE TOPIC

Assessment Due

1

Introduction to statistics

 

2

Graphing data

 

3

Numerical summaries

 

4

The Normal distribution

 

5

Distribution of means and proportions

 

6

Confidence intervals

Assignment 1 due by 5pm April 1st

  Semester Break

 

 7 One sample hypothesis test for a population mean  

8

Hypothesis tests for comparing population means

Class Test (held during Tutorials in Week 8)

9

Simple linear regression (Part 1)

 

10

Simple linear regression (Part 2)

 

11

Hypothesis tests for a population proportion: z-test and chi-squared goodness-of fit

Assignment 2 due by 5pm 20th May

12

Chi-squared test of independence

Statistics Report due by 5pm 27th May

13

Review of STAT670

 

 

Learning and Teaching Activities

Lectures

Lectures begin in Week 1. Copies of the lecture slides will be made available via iLearn. The lectures are also recorded via ‘echo360’, and can be accessed on iLearn (under Echo Recordings). Students should print out the lecture slicdes and watch the recordings with the slides handy.

Tutorials and Practicals

Completion of tutorials and practicals is compulsory. Both tutorials and practicals begin in Week 2. Each tutorial and practical is based on work from the previous week's lecture. The aim of tutorials and practicals is to practice techniques and to understand concepts taught in lectures. Material will be made available via iLearn.

Help with STAT670 related administrative matters

For help with STAT670 related administrative matters students should contact Victoria Park, the STAT670 admin officer, via stat670.admin@mq.edu.au

Staff consultation (office) hours

Members of the Statistics Department have consultation hours each week when they are available to help students enrolled in Introductory Statistics. These consultation hours will be listed on iLearn and on the Statistics Department website. If you are locally based you may walk in at those times, no appointment necessary. External students should be sure to seek help via the Discussion forum if coursework problems are encountered and it is not possible to visit the University for assistance.

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:

Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html

Assessment Policy  http://mq.edu.au/policy/docs/assessment/policy.html

Grading Policy http://mq.edu.au/policy/docs/grading/policy.html

Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html

Grievance Management Policy http://mq.edu.au/policy/docs/grievance_management/policy.html

Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.

In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/

Results

Results shown in iLearn, or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Learning Skills

Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.

Student Services and Support

Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.

Student Enquiries

For all student enquiries, visit Student Connect at ask.mq.edu.au

IT Help

For help with University computer systems and technology, visit http://informatics.mq.edu.au/help/

When using the University's IT, you must adhere to the Acceptable Use Policy. The policy applies to all who connect to the MQ network including students.

Graduate Capabilities

Creative and Innovative

Our graduates will also be capable of creative thinking and of creating knowledge. They will be imaginative and open to experience and capable of innovation at work and in the community. We want them to be engaged in applying their critical, creative thinking.

This graduate capability is supported by:

Learning outcomes

  • Interpret statistical results and write a statistics report based on the results of a statistical analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.

Assessment tasks

  • Assignment 1
  • Assignment 2
  • Statistics Report
  • Final Examination

Learning and teaching activities

  • Lectures begin in Week 1. Copies of the lecture slides will be made available via iLearn. The lectures are also recorded via ‘echo360’, and can be accessed on iLearn (under Echo Recordings). Students should print out the lecture slicdes and watch the recordings with the slides handy.
  • Completion of tutorials and practicals is compulsory. Both tutorials and practicals begin in Week 2. Each tutorial and practical is based on work from the previous week's lecture. The aim of tutorials and practicals is to practice techniques and to understand concepts taught in lectures. Material will be made available via iLearn.

Capable of Professional and Personal Judgement and Initiative

We want our graduates to have emotional intelligence and sound interpersonal skills and to demonstrate discernment and common sense in their professional and personal judgement. They will exercise initiative as needed. They will be capable of risk assessment, and be able to handle ambiguity and complexity, enabling them to be adaptable in diverse and changing environments.

This graduate capability is supported by:

Learning outcomes

  • Be able to check the assumptions underlying the statistical models; carry out a statistical analysis and draw conclusions from the results of data analysis.
  • Interpret statistical results and write a statistics report based on the results of a statistical analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.

Assessment tasks

  • Assignment 1
  • Assignment 2
  • Statistics Report
  • Final Examination

Learning and teaching activities

  • Lectures begin in Week 1. Copies of the lecture slides will be made available via iLearn. The lectures are also recorded via ‘echo360’, and can be accessed on iLearn (under Echo Recordings). Students should print out the lecture slicdes and watch the recordings with the slides handy.
  • Completion of tutorials and practicals is compulsory. Both tutorials and practicals begin in Week 2. Each tutorial and practical is based on work from the previous week's lecture. The aim of tutorials and practicals is to practice techniques and to understand concepts taught in lectures. Material will be made available via iLearn.

Commitment to Continuous Learning

Our graduates will have enquiring minds and a literate curiosity which will lead them to pursue knowledge for its own sake. They will continue to pursue learning in their careers and as they participate in the world. They will be capable of reflecting on their experiences and relationships with others and the environment, learning from them, and growing - personally, professionally and socially.

This graduate capability is supported by:

Learning outcome

  • Identify and apply appropriate statistical methods to address a range of practical problems.

Assessment tasks

  • Assignment 2
  • Class Test
  • Statistics Report
  • Final Examination

Learning and teaching activities

  • Lectures begin in Week 1. Copies of the lecture slides will be made available via iLearn. The lectures are also recorded via ‘echo360’, and can be accessed on iLearn (under Echo Recordings). Students should print out the lecture slicdes and watch the recordings with the slides handy.
  • Completion of tutorials and practicals is compulsory. Both tutorials and practicals begin in Week 2. Each tutorial and practical is based on work from the previous week's lecture. The aim of tutorials and practicals is to practice techniques and to understand concepts taught in lectures. Material will be made available via iLearn.

Discipline Specific Knowledge and Skills

Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.

This graduate capability is supported by:

Learning outcomes

  • Manipulate, classify and summarise different types of data both graphically and numerically.
  • Deeply understand and apply appropriate statistical techniques for analysis of various types of data.
  • Use Minitab to organise, manipulate, summarise and analyse data.
  • Be able to check the assumptions underlying the statistical models; carry out a statistical analysis and draw conclusions from the results of data analysis.
  • Interpret statistical results and write a statistics report based on the results of a statistical analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.
  • Have a deep understanding of the differences between one-sample and two-sample statistical tests and be able to apply the tests in statistical analysis.

Assessment tasks

  • Assignment 1
  • Assignment 2
  • Class Test
  • Statistics Report
  • Final Examination

Learning and teaching activities

  • Lectures begin in Week 1. Copies of the lecture slides will be made available via iLearn. The lectures are also recorded via ‘echo360’, and can be accessed on iLearn (under Echo Recordings). Students should print out the lecture slicdes and watch the recordings with the slides handy.
  • Completion of tutorials and practicals is compulsory. Both tutorials and practicals begin in Week 2. Each tutorial and practical is based on work from the previous week's lecture. The aim of tutorials and practicals is to practice techniques and to understand concepts taught in lectures. Material will be made available via iLearn.

Critical, Analytical and Integrative Thinking

We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.

This graduate capability is supported by:

Learning outcomes

  • Deeply understand and apply appropriate statistical techniques for analysis of various types of data.
  • Use Minitab to organise, manipulate, summarise and analyse data.
  • Be able to check the assumptions underlying the statistical models; carry out a statistical analysis and draw conclusions from the results of data analysis.
  • Interpret statistical results and write a statistics report based on the results of a statistical analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.
  • Have a deep understanding of the differences between one-sample and two-sample statistical tests and be able to apply the tests in statistical analysis.

Assessment tasks

  • Assignment 1
  • Assignment 2
  • Class Test
  • Statistics Report
  • Final Examination

Learning and teaching activities

  • Lectures begin in Week 1. Copies of the lecture slides will be made available via iLearn. The lectures are also recorded via ‘echo360’, and can be accessed on iLearn (under Echo Recordings). Students should print out the lecture slicdes and watch the recordings with the slides handy.
  • Completion of tutorials and practicals is compulsory. Both tutorials and practicals begin in Week 2. Each tutorial and practical is based on work from the previous week's lecture. The aim of tutorials and practicals is to practice techniques and to understand concepts taught in lectures. Material will be made available via iLearn.

Problem Solving and Research Capability

Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.

This graduate capability is supported by:

Learning outcomes

  • Deeply understand and apply appropriate statistical techniques for analysis of various types of data.
  • Use Minitab to organise, manipulate, summarise and analyse data.
  • Be able to check the assumptions underlying the statistical models; carry out a statistical analysis and draw conclusions from the results of data analysis.
  • Interpret statistical results and write a statistics report based on the results of a statistical analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.
  • Have a deep understanding of the differences between one-sample and two-sample statistical tests and be able to apply the tests in statistical analysis.

Assessment tasks

  • Assignment 1
  • Assignment 2
  • Class Test
  • Statistics Report
  • Final Examination

Learning and teaching activities

  • Lectures begin in Week 1. Copies of the lecture slides will be made available via iLearn. The lectures are also recorded via ‘echo360’, and can be accessed on iLearn (under Echo Recordings). Students should print out the lecture slicdes and watch the recordings with the slides handy.
  • Completion of tutorials and practicals is compulsory. Both tutorials and practicals begin in Week 2. Each tutorial and practical is based on work from the previous week's lecture. The aim of tutorials and practicals is to practice techniques and to understand concepts taught in lectures. Material will be made available via iLearn.

Effective Communication

We want to develop in our students the ability to communicate and convey their views in forms effective with different audiences. We want our graduates to take with them the capability to read, listen, question, gather and evaluate information resources in a variety of formats, assess, write clearly, speak effectively, and to use visual communication and communication technologies as appropriate.

This graduate capability is supported by:

Learning outcomes

  • Manipulate, classify and summarise different types of data both graphically and numerically.
  • Interpret statistical results and write a statistics report based on the results of a statistical analysis.
  • Identify and apply appropriate statistical methods to address a range of practical problems.

Assessment tasks

  • Assignment 1
  • Assignment 2
  • Statistics Report
  • Final Examination

Learning and teaching activities

  • Lectures begin in Week 1. Copies of the lecture slides will be made available via iLearn. The lectures are also recorded via ‘echo360’, and can be accessed on iLearn (under Echo Recordings). Students should print out the lecture slicdes and watch the recordings with the slides handy.
  • Completion of tutorials and practicals is compulsory. Both tutorials and practicals begin in Week 2. Each tutorial and practical is based on work from the previous week's lecture. The aim of tutorials and practicals is to practice techniques and to understand concepts taught in lectures. Material will be made available via iLearn.

Engaged and Ethical Local and Global citizens

As local citizens our graduates will be aware of indigenous perspectives and of the nation's historical context. They will be engaged with the challenges of contemporary society and with knowledge and ideas. We want our graduates to have respect for diversity, to be open-minded, sensitive to others and inclusive, and to be open to other cultures and perspectives: they should have a level of cultural literacy. Our graduates should be aware of disadvantage and social justice, and be willing to participate to help create a wiser and better society.

This graduate capability is supported by:

Learning outcome

  • Identify and apply appropriate statistical methods to address a range of practical problems.

Assessment tasks

  • Assignment 2
  • Statistics Report
  • Final Examination

Learning and teaching activities

  • Lectures begin in Week 1. Copies of the lecture slides will be made available via iLearn. The lectures are also recorded via ‘echo360’, and can be accessed on iLearn (under Echo Recordings). Students should print out the lecture slicdes and watch the recordings with the slides handy.
  • Completion of tutorials and practicals is compulsory. Both tutorials and practicals begin in Week 2. Each tutorial and practical is based on work from the previous week's lecture. The aim of tutorials and practicals is to practice techniques and to understand concepts taught in lectures. Material will be made available via iLearn.

Socially and Environmentally Active and Responsible

We want our graduates to be aware of and have respect for self and others; to be able to work with others as a leader and a team player; to have a sense of connectedness with others and country; and to have a sense of mutual obligation. Our graduates should be informed and active participants in moving society towards sustainability.

This graduate capability is supported by:

Learning outcome

  • Identify and apply appropriate statistical methods to address a range of practical problems.

Assessment tasks

  • Assignment 2
  • Statistics Report
  • Final Examination

Learning and teaching activities

  • Lectures begin in Week 1. Copies of the lecture slides will be made available via iLearn. The lectures are also recorded via ‘echo360’, and can be accessed on iLearn (under Echo Recordings). Students should print out the lecture slicdes and watch the recordings with the slides handy.
  • Completion of tutorials and practicals is compulsory. Both tutorials and practicals begin in Week 2. Each tutorial and practical is based on work from the previous week's lecture. The aim of tutorials and practicals is to practice techniques and to understand concepts taught in lectures. Material will be made available via iLearn.