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BIOL235 – Experimental Design and Data Analysis for Biology

2017 – S2 Day

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor
Drew Allen
Contact via drew.allen@mq.edu.au
E8B217
Thursday 2-3pm, or by appointment
Credit points Credit points
3
Prerequisites Prerequisites
12cp at 100 level or above including ((STAT170(P) or STAT150 or STAT171) and (3cp(P) in BBE or BIOL units))
Corequisites Corequisites
Co-badged status Co-badged status
BIOL603
Unit description Unit description
Biological organisms are inherently variable, which means that practicing biologists need a solid grasp of how to design experiments and how to interpret the resulting data. This unit provides a foundation in the principles of experimental design and data analysis for biology. The unit is taught by biology staff and draws on research carried out in the Department of Biological Sciences. Students also learn the overall process of asking and answering questions in biology. Students learn a range of common data analysis techniques, and how to interpret the outcomes of these analyses. There is a strong emphasis on critically evaluating biological studies and identifying sound conclusions and not-so-sound conclusions. This unit is strongly recommended for students planning a career in biology or environmental science.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at http://students.mq.edu.au/student_admin/enrolmentguide/academicdates/

Learning Outcomes

  1. Develop testable hypotheses from general scientific questions
  2. Design an unconfounded experiment to test a given scientific hypothesis
  3. Identify dependent and independent variables and recognize different types of variable
  4. Choose an appropriate statistical test to analyse experimental data
  5. Carry out a range of commonly-used statistical tests using the computer package R
  6. Correctly interpret results from statistical tests
  7. Clearly present outcomes from experiments, using figures, tables and text
  8. Critically evaluate other studies
  9. Identify possible confounding factors
  10. Evaluate whether statistical tests have been correctly applied and interpreted

General Assessment Information

Assessment details

Details of assessments will be provided on iLearn and in class.

 

Assignment submission

The Experiment Report must be submitted digitally through the Turnitin submission link on iLearn. All assessments need to be written in the students own words. 

 

Academic honesty

The Experiment Report need to be written in the students own words. The penalties imposed by the University for plagiarism are serious and may include expulsion from the University. Evidence of plagiarism will be dealt with according to University policy. Penalties for plagiarism will be imposed and clearly defined in marking guides. Further penalties imposed by the Faculty disciplinary committee may range from a loss of all marks and awarding of a zero depending on the circumstances. 

 

Extensions, penalties and Disruptions to Studies

If an assignment is submitted late, a penalty of 5% of the mark will be deducted per day that any work is submitted late (i.e. 10 days late = 50% of marks available).

If you experience a serious and unavoidable disruption to your studies and require an extension for an assessment please submit a Disruptions to Studies notification via ask.mq.edu.au with supporting documentation, and a Professional Authority Form completed by your health care professional. If you anticipate a potentially serious and unavoidable disruption (e.g. upcoming surgery) speak to the unit convenor early and apply for an extension before the due date.

 

Unit completion

To pass this unit, the student needs to achieve an overall minimum grade of 50%. The student must also pass both hurdle assessments, the exam of basic knowledge and the experimental report.

Assessment Tasks

Name Weighting Due
Weekly Quiz 15% Monday 5 pm, weekly
Exam of Basic Stats Knowledge 5% Week 4
Mid-semester Exam 15% Week 8
Experiment Report 20% Friday 27 October, 5 pm
Final Exam 45% Examination Period

Weekly Quiz

Due: Monday 5 pm, weekly
Weighting: 15%

Every week there will be an on-line quiz with example problems to complete. These problems will be based on that week's lectures and practicals and provide a chance for you to practice applying the concepts you have learned. It is strongly recommended that you make a serious effort to complete these quizzes.


This Assessment Task relates to the following Learning Outcomes:
  • Develop testable hypotheses from general scientific questions
  • Design an unconfounded experiment to test a given scientific hypothesis
  • Identify dependent and independent variables and recognize different types of variable
  • Choose an appropriate statistical test to analyse experimental data
  • Carry out a range of commonly-used statistical tests using the computer package R
  • Correctly interpret results from statistical tests
  • Clearly present outcomes from experiments, using figures, tables and text
  • Critically evaluate other studies
  • Identify possible confounding factors
  • Evaluate whether statistical tests have been correctly applied and interpreted

Exam of Basic Stats Knowledge

Due: Week 4
Weighting: 5%

You will be tested on your knowledge of basic statistical concepts and skills that were taught in STAT170. The test will be delivered as an online quiz through iLearn. Important: This is a hurdle assessment, meaning that you will not pass the unit if you do not pass this assessment. If you fail, but receive a mark of at least 40%, you will be given a second opportunity to take the exam.


This Assessment Task relates to the following Learning Outcomes:
  • Identify dependent and independent variables and recognize different types of variable
  • Choose an appropriate statistical test to analyse experimental data
  • Correctly interpret results from statistical tests
  • Identify possible confounding factors
  • Evaluate whether statistical tests have been correctly applied and interpreted

Mid-semester Exam

Due: Week 8
Weighting: 15%

You will be tested on your knowledge of lecture material for weeks 1-6 in Week 8 (following semester break). This test will be delivered as an online assignment accessible through iLearn.


This Assessment Task relates to the following Learning Outcomes:
  • Identify dependent and independent variables and recognize different types of variable
  • Choose an appropriate statistical test to analyse experimental data
  • Correctly interpret results from statistical tests
  • Critically evaluate other studies
  • Identify possible confounding factors
  • Evaluate whether statistical tests have been correctly applied and interpreted

Experiment Report

Due: Friday 27 October, 5 pm
Weighting: 20%

You will design, conduct and analyse data for an experiment of your own. You will be given a range of alternative experimental questions to choose from. You will need to pick a question, design and carry out an experiment addressing that question, then write up the results in the form of the methods and results sections of a scientific paper. Full details will be given at the start of semester. Important: This is a hurdle assessment, meaning that you will not pass the unit if you do not pass this assessment. If you fail on your first submission, but receive a mark of at least 40%, you will be given a second opportunity to submit the assignment for re-grading.


This Assessment Task relates to the following Learning Outcomes:
  • Develop testable hypotheses from general scientific questions
  • Design an unconfounded experiment to test a given scientific hypothesis
  • Identify dependent and independent variables and recognize different types of variable
  • Choose an appropriate statistical test to analyse experimental data
  • Carry out a range of commonly-used statistical tests using the computer package R
  • Correctly interpret results from statistical tests
  • Clearly present outcomes from experiments, using figures, tables and text

Final Exam

Due: Examination Period
Weighting: 45%

The final exam will be held during the Semester 2 Exam Period and will be 2 hr (plus 10 min reading time). Please consult the University Handbook to determine the commencement and finishing dates of the compulsory exam period. More details on the structure of the final exam will be given closer to the time.


This Assessment Task relates to the following Learning Outcomes:
  • Identify dependent and independent variables and recognize different types of variable
  • Choose an appropriate statistical test to analyse experimental data
  • Correctly interpret results from statistical tests
  • Critically evaluate other studies
  • Identify possible confounding factors
  • Evaluate whether statistical tests have been correctly applied and interpreted

Delivery and Resources

CLASSES

Internal Students

Contact hours consist of 2 lectures and one 2-hour practical per week.

* Lecture and practical times will be available on iLearn.

External Students

Lecture material will be placed online for access by external students.

Practicals will take place online on Monday and Tuesday evenings from 7 - 9pm. The link to the online practical session will be made available on iLearn.

 

REQUIRED AND RECOMMENDED TEXTS AND/OR MATERIALS

Recommended Reading

  • Statistics explained: an introductory guide for life scientists. 2nd ed, Steve McKillup 2011 (MyiLibrary Online access)

Other suggested reading: 

Online: The Handbook of Biological Statistics http://udel.edu/~mcdonald/statintro.html is an excellent resource which covers many of the same topics as BIOL235 in a very accessible way.

Library: The library holds a wide range of books covering stats for biologists at different levels. Some favourites from the biology staff are listed below in approximate order of difficulty. These books will be placed in reserve.

  • Practical statistics for field biology Jim Fowler, Louis Cohen, Phil Jarvis 1998 (QH318.5 .F68 1998)
  • Statistics for terrified biologists Helmut F. van Emden (QH323.5 .V33 2008)
  • The analysis of biological data. Whitlock & Schluter (QH323.5 W48 2009)
  • Experiments in ecology : their logical design and interpretation using analysis of variance A. J. Underwood 1997 (QH541.24 .U54 1997)
  • A primer of ecological statistics Nicholas J. Gotelli, Aaron M. Ellison 2004 (QH541.15.S72 G68 2004)
  • Experimental design and data analysis for biologists G. P. Quinn, Michael J. Keough 2002 MyiLibrary Online access

UNIT WEBPAGE AND TECHNOLOGY USED AND REQUIRED

Website

Lecture graphics and iLectures will be available on iLearn (http://ilearn.mq.edu.au). iLearn is a web-based communication package and can be accessed by most web browsers from inside or outside the University. iLearn and email will be the primary methods of communication in this subject. You are expected to use iLearn for:

  • Regularly checking subject announcements;
  • Downloading lecture, tutorial and reference materials;
  • Checking your grades.

How do you log in? The URL for the iLearn log in page is: http://ilearn.mq.edu.au/.

You must log in to iLearn each time you use it. Your user name is your student number, and your password is your myMQ student portal password, provided upon enrolment (unless you've changed it). If you are having trouble accessing your online unit due to a disability or health condition, please go to the Student Services Website at http://sss.mq.edu.au/equity/about for information on how to get assistance.

If you are having problems logging on, that is, if you cannot log in after ensuring you have entered your username and password correctly, you should contact Student IT Help, Phone: (02) 9850 4357 (in Sydney) or 1 800 063 191 (outside Sydney).

Software

Lecture examples, quizzes, and tutorials will be carried out using the computer programs R (http://cran.r-project.org/) and R Studio (https://www.rstudio.com/products/rstudio/download/), both of which are freely available for download.

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_2016.html

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

Complaint Management Procedure for Students and Members of the Public http://www.mq.edu.au/policy/docs/complaint_management/procedure.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 Enquiry Service

For all student enquiries, visit Student Connect at ask.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.

Graduate Capabilities

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

  • Choose an appropriate statistical test to analyse experimental data
  • Carry out a range of commonly-used statistical tests using the computer package R

Assessment tasks

  • Weekly Quiz
  • Exam of Basic Stats Knowledge
  • Mid-semester Exam
  • Final Exam

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

  • Develop testable hypotheses from general scientific questions
  • Design an unconfounded experiment to test a given scientific hypothesis
  • Carry out a range of commonly-used statistical tests using the computer package R
  • Correctly interpret results from statistical tests

Assessment tasks

  • Weekly Quiz
  • Exam of Basic Stats Knowledge
  • Experiment Report
  • Final Exam

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 outcome

  • Clearly present outcomes from experiments, using figures, tables and text

Assessment tasks

  • Mid-semester Exam
  • Experiment Report

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

  • Correctly interpret results from statistical tests
  • Critically evaluate other studies
  • Identify possible confounding factors
  • Evaluate whether statistical tests have been correctly applied and interpreted

Assessment task

  • Experiment Report

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

  • Develop testable hypotheses from general scientific questions
  • Design an unconfounded experiment to test a given scientific hypothesis
  • Identify dependent and independent variables and recognize different types of variable
  • Choose an appropriate statistical test to analyse experimental data
  • Carry out a range of commonly-used statistical tests using the computer package R
  • Correctly interpret results from statistical tests
  • Critically evaluate other studies
  • Identify possible confounding factors
  • Evaluate whether statistical tests have been correctly applied and interpreted

Assessment tasks

  • Weekly Quiz
  • Exam of Basic Stats Knowledge
  • Experiment Report

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

  • Develop testable hypotheses from general scientific questions
  • Design an unconfounded experiment to test a given scientific hypothesis

Assessment task

  • Experiment Report

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 outcomes

  • Critically evaluate other studies
  • Identify possible confounding factors
  • Evaluate whether statistical tests have been correctly applied and interpreted

Assessment task

  • Experiment Report

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 outcomes

  • Critically evaluate other studies
  • Identify possible confounding factors
  • Evaluate whether statistical tests have been correctly applied and interpreted

Assessment task

  • Experiment Report

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 outcomes

  • Critically evaluate other studies
  • Identify possible confounding factors
  • Evaluate whether statistical tests have been correctly applied and interpreted

Assessment tasks

  • Exam of Basic Stats Knowledge
  • Experiment Report

Changes from Previous Offering

There is now a hurdle exam covering basic statistical knowledge.

Changes since First Published

Date Description
04/08/2017 Removal of non-teaching staff
25/07/2017 Changed due date for weekly quizzes from Friday to Monday