Students

FOSE1015 – Statistical Concepts for Science

2021 – Session 1, Special circumstances

Notice

As part of Phase 3 of our return to campus plan, most units will now run tutorials, seminars and other small group activities on campus, and most will keep an online version available to those students unable to return or those who choose to continue their studies online.

To check the availability of face-to-face and online activities for your unit, please go to timetable viewer. To check detailed information on unit assessments visit your unit's iLearn space or consult your unit convenor.

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Lecturer
Karol Binkowski
Administrative assistance
Karol Binkowski
Huan Lin
Credit points Credit points
10
Prerequisites Prerequisites
Corequisites Corequisites
Co-badged status Co-badged status
It is co-badged with STAT1170.
Unit description Unit description

This unit has an online offering for S2 which is synchronous, meaning there will be set times to attend online lectures and tutorials.

This unit provides a broad introduction to statistical concepts and data analysis techniques. You will develop an understanding of statistical practice through a study of those techniques most commonly used in the sciences, social sciences and humanities. Topics covered in this unit include data collection methods, data quality, data summarisation, and statistical models such as 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. However, no prior computing knowledge is assumed. This unit introduces vital skills for tertiary learning and explores their relationship to success in future careers.

Important Academic Dates

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

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: Even if you are enrolled in online or special circumstances 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 or special circumstances mode (although you should work through this material to develop your understanding). Every student should enrol in a Practical class and an SGTA class. You may enrol in a class on campus if you plan to attend in person. Otherwise, please enrol in the online classes.

TEST SUBMISSION: Each statistics module's tests will be online, via the iLearn page. For some of the tests, multiple attempts are allowed; in this case, the highest mark counts toward the student's grade. For each statistics module, at least 50% of the available marks must be scored in order to pass the unit.

A student who does not pass any statistics module 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.

Assessment Tasks

Name Weighting Hurdle Due
Participation in practical classes 0% Yes Weeks 1 to 11
Module 5 test 20% Yes Week 12
Module 2 test 20% Yes Week 6
Module 3 test 20% Yes Week 8
Participation in lecture activities 0% Yes Weeks 1 to 10
Module 4 test 20% Yes Week 10
Module 1 Test 20% Yes Week 4
Foundation activities 0% Yes Throughout the semester

Participation in practical classes

Assessment Type 1: Participatory task
Indicative Time on Task 2: 0 hours
Due: Weeks 1 to 11
Weighting: 0%
This is a hurdle assessment task (see assessment policy for more information on hurdle assessment tasks)

 

Students are expected to demonstrate their ability to engage with the unit by participating in practical classes

 


On successful completion you will be able to:
  • Demonstrate foundational employability and self-directed learning skills, including recording academic achievements to link university study to future careers.

Module 5 test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 2 hours
Due: Week 12
Weighting: 20%
This is a hurdle assessment task (see assessment policy for more information on hurdle assessment tasks)

 

This quiz will test the ability of students to answer research questions about the appropriateness of models for a categorical random variable, and the independence of two categorical random variables.

 


On successful completion you will be able to:
  • Organise and summarise data graphically and numerically.
  • Analyse and solve problems about distributions and sampling distributions.
  • Evaluate and apply statistical strategies to answer a research question.
  • Draw conclusions from the results of a statistical analysis.
  • Evaluate the appropriateness of statistical methodologies when analysing a variety of problems arising from other fields of research.

Module 2 test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 2 hours
Due: Week 6
Weighting: 20%
This is a hurdle assessment task (see assessment policy for more information on hurdle assessment tasks)

 

This quiz will test the ability of students to analyse and solve statistical problems leveraging the properties of distributions and sampling distributions.

 


On successful completion you will be able to:
  • Organise and summarise data graphically and numerically.
  • Analyse and solve problems about distributions and sampling distributions.
  • Evaluate the appropriateness of statistical methodologies when analysing a variety of problems arising from other fields of research.

Module 3 test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 2 hours
Due: Week 8
Weighting: 20%
This is a hurdle assessment task (see assessment policy for more information on hurdle assessment tasks)

 

This quiz will test the ability of students to answer research questions about population means.

 


On successful completion you will be able to:
  • Organise and summarise data graphically and numerically.
  • Analyse and solve problems about distributions and sampling distributions.
  • Evaluate and apply statistical strategies to answer a research question.
  • Draw conclusions from the results of a statistical analysis.
  • Evaluate the appropriateness of statistical methodologies when analysing a variety of problems arising from other fields of research.

Participation in lecture activities

Assessment Type 1: Participatory task
Indicative Time on Task 2: 0 hours
Due: Weeks 1 to 10
Weighting: 0%
This is a hurdle assessment task (see assessment policy for more information on hurdle assessment tasks)

 

Students are expected to demonstrate their ability to engage with the unit by participating in lecture activities.

 


On successful completion you will be able to:
  • Demonstrate foundational employability and self-directed learning skills, including recording academic achievements to link university study to future careers.

Module 4 test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 2 hours
Due: Week 10
Weighting: 20%
This is a hurdle assessment task (see assessment policy for more information on hurdle assessment tasks)

 

This quiz will test the ability of students to answer research questions about the linear relationship between two numerical random variables.

 


On successful completion you will be able to:
  • Organise and summarise data graphically and numerically.
  • Analyse and solve problems about distributions and sampling distributions.
  • Evaluate and apply statistical strategies to answer a research question.
  • Draw conclusions from the results of a statistical analysis.
  • Evaluate the appropriateness of statistical methodologies when analysing a variety of problems arising from other fields of research.

Module 1 Test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 2 hours
Due: Week 4
Weighting: 20%
This is a hurdle assessment task (see assessment policy for more information on hurdle assessment tasks)

 

This quiz will test the ability of students to summarise a data set numerically and graphically, and to understand and interpret the output of such analyses.

 


On successful completion you will be able to:
  • Organise and summarise data graphically and numerically.
  • Evaluate the appropriateness of statistical methodologies when analysing a variety of problems arising from other fields of research.

Foundation activities

Assessment Type 1: Participatory task
Indicative Time on Task 2: 0 hours
Due: Throughout the semester
Weighting: 0%
This is a hurdle assessment task (see assessment policy for more information on hurdle assessment tasks)

 

Activities related to foundational employability and self-directed learning skills

 


On successful completion you will be able to:
  • Demonstrate foundational employability and self-directed learning skills, including recording academic achievements to link university study to future careers.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Learning Skills Unit for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

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 1–11. (Week 1 will introduce the employability module.)

Some activities will be available in connection to the employability modules, especially near the end of semester. Details will be announced via iLearn.

Assistance

For help with any matters related to this unit, students should contact the appropriate department staff, by emailing stat1170.admin@mq.edu.au.

Required and Recommended Texts and/or Materials

  • A calculator with statistics mode may be useful during lectures.
  • 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 for this unit:

  • Modern Statistics: An introduction, Don McNeil and Jenny Middledorp (ISBN 9781486007011). This can be purchased in hard copy from www.booktopia.com.au/coop 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 (a version of Moodle) is used for delivery of course material and can be accessed at: http://ilearn.mq.edu.au.

Prizes

The 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

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/admin/other-resources/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 Enquiry Service

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

Equity 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.

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 was been adapted from an earlier unit, STAT170, in Semester 1 of 2020. For the current offering, there are few changes: just some minor adjustments to the assessment structure.