Students

STAT1170 – Introductory Statistics

2020 – Session 1, Online with attendance for exam, Exam centre within Australia

Coronavirus (COVID-19) Update

Due to the Coronavirus (COVID-19) pandemic, any references to assessment tasks and on-campus delivery may no longer be up-to-date on this page.

Students should consult iLearn for revised unit information.

Find out more about the Coronavirus (COVID-19) and potential impacts on staff and students

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor/Lecturer
David Bulger
please refer to iLearn
Lecturer
Karol Binkowski
Administrative assistance
Academic assistance
Christine Hale
Credit points Credit points
10
Prerequisites Prerequisites
Corequisites Corequisites
Co-badged status Co-badged status
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 and proportions. 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:

  • ULO1: Organise and summarise data graphically and numerically.
  • ULO2: Analyse and solve problems about distributions and sampling distributions.
  • ULO3: Evaluate and apply statistical strategies to answer a research question.
  • ULO4: Draw conclusions from the results of a statistical analysis.
  • ULO5: Evaluate the appropriateness of statistical methodologies when analysing a variety of problems arising from other fields of research.
  • ULO6: Demonstrate foundational employability and self-directed learning skills, including recording academic achievements to link university study to future careers.

Assessment Tasks

Coronavirus (COVID-19) Update

Assessment details are no longer provided here as a result of changes due to the Coronavirus (COVID-19) pandemic.

Students should consult iLearn for revised unit information.

Find out more about the Coronavirus (COVID-19) and potential impacts on staff and students

General Assessment Information

The data in the above table's "Estimated Time on Task" column is automatically generated, and potentially confusing. The times given for the tests (2 hours each) are just estimates; for each student, this will depend on how many times the test is attempted. The times allocated to activity participation (each 0 hours) should be ignored.

HURDLES: All assessment tasks are hurdle requirements to pass this unit.  These can be different for internal and external students. Details will be provided on the iLearn page for the unit.

ATTENDANCE and PARTICIPATION: Online Students - Even though you are enrolled in online mode, you are required to engage with the lecture material each week. This will be monitored via short weekly participation quizzes; see the iLearn site for details. Please contact the unit convenor as soon as possible if you have difficulty completing any of these participation quizzes on time. There may be alternatives available to make up the work. If there are circumstances that mean you will miss a participation quiz, you can apply for Special Consideration via ask.mq.edu.au.

There is no participation requirement for Practicals or SGTAs for students enrolled in online mode (although you should work through this material to improve your understanding).

TEST SUBMISSION: Each module's test will be online, via the iLearn page. Students may attempt each test as many times as they choose, prior to the end of Week 13, with the highest mark counting toward the student's grade. For each test, a serious attempt (defined as a mark of at least 30%) must be made by the deadline in order to pass the unit.

A student who does not make a serious attempt (that is, score at least 30%) on any test by its deadline will fail the unit, unless Special Consideration is granted. If you miss a test deadline due to circumstances out of your control, you may be eligible to apply for Special Consideration via ask.mq.edu.au.

EMPLOYABILITY SKILLS: This unit has been designed so that 20% of student workload is allocated to employability skills. The employability skills modules are not graded, but the modules are hurdle tasks: you must complete the activities as outlined in order to pass this unit. Some activities will be automatically graded, but all will ask you to apply the modules to your work in this unit, general university studies and your personal goals. You will be informed of any due dates, but most modules can be completed in your own time.  See your iLearn unit for detailed information on how to complete the skills modules.

FINAL EXAM POLICY: There is no final exam for this unit.

Delivery and Resources

Coronavirus (COVID-19) Update

Any references to on-campus delivery below may no longer be relevant due to COVID-19.

Please check here for updated delivery information: https://ask.mq.edu.au/account/pub/display/unit_status

Classes

The statistics content will be delivered in classes from Week 1 to Week 11. Specifically, students should work through the following material on a weekly basis:

  • A 2-hour lecture – recorded Weeks 1–10.
  • A 1-hour SGTA on the topics of the previous lecture – Weeks 1–11. (Week 1 will introduce the employability module.)
  • A 1-hour practical on the topics of the previous one or two lectures – Weeks 2–11.

The details of activities in the employability module will be announced via iLearn.

Assistance

For help with any matters related to this unit, students should contact the appropriate department staff:

  • for administrative matters, email stat1170.admin@mq.edu.au.
  • for academic matters (e.g., help understanding the material, or questions about marks), email your lecturers at stat1170.academic@mq.edu.au.

Required and Recommended Texts and/or Materials

  • A calculator with statistics mode will be essential.
  • Software:
    • The software used in this unit is Excel, the spreadsheet application from Microsoft's Office suite. For students with Mac or Windows computers, this application can be downloaded from the student portal. This can be accessed from the web page for Student IT services: http://students.mq.edu.au/it_services/.  Students using other operating systems might find Google Sheets or OpenOffice Calc to be a workable alternative.

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).

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

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

Prizes

Don McNeil Prize for Introductory Statistics is named in honour of the foundation Professor of Statistics at Macquarie University. The prize is awarded twice per year to the student with the best overall performance in a first-year statistics unit.

Unit Schedule

Coronavirus (COVID-19) Update

The unit schedule/topics and any references to on-campus delivery below may no longer be relevant due to COVID-19. Please consult iLearn for latest details, and check here for updated delivery information: https://ask.mq.edu.au/account/pub/display/unit_status

In Weeks 1–10, the lectures will introduce the following topics. Each topic will be developed in SGTAs and Practicals in the following week.

Week 1 Data, research questions, graphics
Week 2 Numerical data
Week 3 Introduction to distributions
Week 4 Sampling distributions
Week 5 Hypothesis tests for a population mean
Week 6 Comparing population means
Week 7 Simple linear regression
Week 8 Simple linear regression
Week 9 Categorical data analysis
Week 10 Categorical data analysis

Employability activities and assessment will occur throughout the semester, including Weeks 11–13.

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit the Student Policy Gateway (https://students.mq.edu.au/support/study/student-policy-gateway). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

If you would like to see all the policies relevant to Learning and Teaching visit Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/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/study/getting-started/student-conduct​

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) 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 or if you are a Global MBA student contact globalmba.support@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 help you improve your marks and take control of your study.

The Library provides online and face to face support to help you find and use relevant information resources. 

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

If you are a Global MBA student contact globalmba.support@mq.edu.au

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/

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

Changes from Previous Offering

This new unit has been adapted from an earlier unit, STAT170, with some changes. The statistical content has been modernised and streamlined (including changing software to Excel, and avoiding the use of statistical tables) to allow for the new employability content. The assessment structure has been altered, and the final exam eliminated.