- Class Number 2631
- Term Code 3330
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Dr Geoff Kushnick
- Dr Geoff Kushnick
- Class Dates
- Class Start Date 20/02/2023
- Class End Date 26/05/2023
- Census Date 31/03/2023
- Last Date to Enrol 27/02/2023
This course will familiarise students with common methods used in biological anthropology. Specifically, it will deal with issues including the methods of data analysis, data presentation and hypothesis testing within the discipline of biological anthropology. This will be accomplished through students conducting both qualitative and quantitative analysis on an existing data set, and then interpreting the results of that analysis. The main aim of this course is to prepare students for the data analysis portion of their own thesis projects and future research in the discipline.
Upon successful completion, students will have the knowledge and skills to:Upon successful completion of this course, students will have the knowledge and skills to:
- Choose an appropriate research design to answer their research questions;
- Assess a data set and use appropriate techniques to clean it;
- Use descriptive statistics to describe the data set;
- Choose the correct statistical tests to perform significance testing on data sets; and
- Interpret statistical tests and present results in a scientific format.
Students will conduct original analyses with actual biological anthropology data.
Students will be given feedback in the following forms in this course:
- Written feedback on the Project Statement.
- Written feedback on the Presentation.
- Written feedback on the Project Report.
ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.
|Week/Session||Summary of Activities||Assessment|
|1||Identify dataset, topic, and methods-related references in consultation with your supervisor||Readings: Kass et al 2016 + Independent Readings|
|2||Identify dataset, topic, and methods-related references in consultation with your supervisor||Readings: Martin et al 2019 + Independent Readings|
|3||Identify dataset, topic, and methods-related references in consultation with your supervisor||Assessment: Project Statement due Readings: Smith 2019 + Independent Readings|
|4||Work on analyses for project; continue meeting with supervisor; seek additional feedback||Readings: Parker et al 2016 + Independent Readings|
|5||Work on analyses for project; continue meeting with supervisor; seek additional feedback||Readings: Lakens 2022 + Independent Readings|
|6||Work on analyses for project; continue meeting with supervisor; seek additional feedback||Readings: Zuur et al 2010 + Independent Readings|
|7||Work on analyses for project; continue meeting with supervisor; seek additional feedback||Readings: Nakagawa & Freckleton 2010 + Independent Readings|
|8||Work on analyses for project; continue meeting with supervisor; seek additional feedback||Readings: Zuur & Ieno 2016 + Independent Readings|
|9||Write up data analysis project and prepare presentation||Readings: Rougier et al 2014 + Independent Readings|
|10||Write up data analysis project and prepare presentation||Readings: Doubleday & Connell 2017 + Independent Readings|
|11||Write up data analysis project and prepare presentation||Presentation due Readings: Hartley 2008 + Independent Readings|
|12||Write up data analysis project and prepare presentation||Project report due|
|Assessment task||Value||Due Date||Learning Outcomes|
|Project Statement||25 %||08/03/2023||5|
|Project Report||50 %||24/05/2023||1,2,3,4,5|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
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- Student Assessment (Coursework) Policy and Procedure
- Special Assessment Consideration Policy and General Information
- Student Surveys and Evaluations
- Deferred Examinations
- Student Complaint Resolution Policy and Procedure
The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.
Moderation of Assessment
Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.
This course does not include any formal examinations.
Assessment Task 1
Learning Outcomes: 5
During the first few weeks of class, you should be working to Identify a topic, database, and methods-related references for your data analysis project, which is the overarching project for this course. The Project Statement is the first assessment item related to the project. It is highly recommended that you work closely with your honours supervisor to identify a project and the data to be used for this project. You should aim for using good research practices (Parker et al 2016). See Appendix 4 of the ‘Course and Assessment Guide’ for referencing style.
The Project Statement should be 500 words, not counting references.
The data for your data analysis project can be: (a) the data, or a subset of the data, that you will use in your thesis; or (b) a dataset that you will procure from the many freely available ones on the internet and elsewhere. Please read and understand the current rules related to ‘recycling’ of material from the thesis, as this is important in deciding whether you do something that will be slotted into your eventual thesis or something entirely different.
The Project Statement is a statement of the topic, dataset, and initial references you have consulted. The statement of topic should include:
- a brief but detailed outline of the analyses you intend to do for the project and how they relate to your thesis;
- a statement about the dataset which should include the source and brief description of the data, which might include a table of descriptive statistics;
- the initial references should include full bibliographic information for 3 well-chosen references that you have identified as being critical for your project, plus a brief sentence for each explaining why you have chosen it.
The Project Statement is worth 25% of you grade in the course, and will be marked using the following criteria:
- Quality of the statement of topic
- Quality of the statement of data
- Quality of references
- Adherence to assessment instructions
Assessment Task 2
Learning Outcomes: 1,4
You will give a 10-minute presentation about your data analysis project. You should:
- have a first slide with a title and your first and last name (first and last) to show while you provide a brief overview.
- use up to 4 additional slides to supplement the presentation of the details of the project. Slides that feature a well-chosen illustration, or well-crafted tables or figures are ideal.
- not overcrowd your slides.
- use a font size that is readable from a distance for all text parts. In Microsoft PowerPoint, 18-point font is the bare minimum but larger is preferable.
- cite your sources on the slide itself, a references slide, or a separate handout. You should cite at least 5 works related to analysis and methods using the style in Appendix 4 of the course handout. Give the audience a chance to inspect your references.
- practice your presentation ahead of time and speak clearly and confidently.
- speak clearly and with present confidence.
- be ready to transition to conclusions, if you have not already, when you are told you have reached the 1-minute-left mark.
- be prepared to answer questions for around 2 minutes after your presentation.
The Presentation is worth 25% of you grade in the course, and will be marked using the following criteria:
- Quality of project.
- Quality of references.
- Quality of overheads.
- Adherence to assessment instructions.
Assessment Task 3
Learning Outcomes: 1,2,3,4,5
The Project Report is a formal report of the analyses that you have done for the data analysis project for this class. You will have gotten feedback on the topic, data source, and references in an earlier assessment. The analyses you do for your project should be quantitative except under very limited circumstances with written permission from your supervisor provided to the course convenor early in the semester. The project provides a platform for you to practice the sorts of analyses you will do in the thesis, or even to start working on thesis analyses depending on current rules regarding the ‘recycling’ of material from the thesis. That is, if the current rules allow it, you are welcome to use this opportunity to do analyses that will be slotted eventually into the thesis.
The Project Report should be 2500-3000 words (excluding title, figures, figure captions, tables, and references).
The Project Report:
- should reflect an entire semester’s worth of independent work and should be characterized by the appropriate use of quantitative analytical methods of the standard that would be expected in the thesis itself. You should aim for using good research practices (Parker et al 2016). You should consult with your supervisor about this project and you will be provided feedback on your Project Statement in the first half of the semester. You will not be hounded or nudged. You are expected to put in the effort independently and seek input from your supervisor independently.
- does not require a lot of background or theoretical justification. You should provide more detail in the Methods and Results than you provide in the Introduction and Discussion. Ideally, the balance should be something like 10% of the word count to Introduction, 10% to Discussion, and 80% to Methods and Results. The background will be further developed in the thesis.
- should be well formatted, with clear demarcation of paragraphs and section headings. Use a reasonable font and single-spacing, as the paper will be marked electronically.
- must cite 8-15 pieces of appropriate literature, at least 8 going beyond the list of required and indicative readings in the course outline. Preference should be given to references that you have consulted for the analytical and statistical methods and are likely to go beyond those from biological anthropology. Use the citation style from Appendix 4 of the ‘Course and Assessment Guide’.
- must have at least 1 table and 1 figure in the paper, but no more than two of each. Each should be labelled and include a numbered and descriptive caption. Each should be referred to in text at least once. Do not cut and paste output from statistical software.
- should have a clear and concise title that reflects your specific topic.
The Project Report is worth 50% of you grade in the course, and will be marked using the following criteria:
- Quality of the project
- Quality of the writing
- Quality of the references
- Conformity to assessment instructions
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You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) as submission must be through Turnitin.
For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.
Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.
Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.
All assessments are “returned” via Turnitin. That is, your mark and feedback for each assignment will be entered into Turnitin. When the marked assessments are released, you will be able to see your mark and feedback in Turnitin. The approximate dates for the return of assessments is included in the Course Overview section of this outline.
Extensions and Penalties
Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.
Resubmission of Assignments
Resubmission is not allowed.
Distribution of grades policy
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Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.
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Dr Geoff Kushnick
Dr Geoff Kushnick