- Class Number 2710
- Term Code 3230
- Class Info
- Unit Value 6 units
- Mode of Delivery In-Person and Online
- Dr Geoff Kushnick
- Dr Geoff Kushnick
- Class Dates
- Class Start Date 21/02/2022
- Class End Date 27/05/2022
- Census Date 31/03/2022
- Last Date to Enrol 28/02/2022
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 be given written feedback on each of the assessment items. They can also seek verbal feedback in office hours from the convenor and/or their supervisor.
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 for project in consultation with your supervisor|
|2||Identify dataset, topic, and methods-related references for project in consultation with your supervisor|
|3||Identify dataset, topic, and methods-related references for project in consultation with your supervisor||Project Statement due|
|4||Work on analyses for project; make appointment with and meet with Statistical Consulting Unit (optional)|
|5||Work on analyses for project; make appointment with and meet with Statistical Consulting Unit (optional)|
|6||Work on analyses for project; make appointment with and meet with Statistical Consulting Unit (optional)|
|9||Write up data analysis project and prepare presentation|
|10||Write up data analysis project and prepare presentation|
|11||Write up data analysis project and prepare presentation||Presentation due|
|12||Write up data analysis project and prepare presentation||Project Report due|
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Project Statement||25 %||10/03/2021||24/03/2021||1, 4|
|Presentation||25 %||17/05/2021||01/06/2021||1, 4|
|Project Report||50 %||03/06/2021||17/06/2021||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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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 Academic Integrity . In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.
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.
Assessment Task 1
Learning Outcomes: 1, 4
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.
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 500-word 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; the statement of dataset 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.
This assessment will be marked on the following criteria:
- Quality of statement of topic
- Quality of statement if data
- Quality of references
- Adherence to assessment instructions
Assessment Task 2
Learning Outcomes: 1, 4
You will give a polished 8-minute presentation in class about your Data Analysis Project. In your presentation, you should:
- have a first slide with your name (first and last) and title of your talk to show while you provide a brief overview of your project.
- use additional slides to supplement the presentation of the details of the project. The ideal number of slides in no more than 4 (which is 2 minutes per slide). 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 part. At least 18-pt font (preferably larger) for all text parts is recommended. Note that this assumes you are using Powerpoint. Other software may require larger fonts for readability.
- cite your sources on the slide itself, on a references slide, or in a separate handout. You should cite at least 5 works related to analysis and methods using APA format. Do not zip past references. Give the audience a chance to inspect them.
- practice your presentation ahead of time.
- speak clearly and present with 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.
You will be marked based on the following criteria:
- Quality of project.
- Quality of references.
- Quality of overheads.
- Conformity to instructions.
Assessment Task 3
Learning Outcomes: 1, 2, 3, 4, 5
The Project Report is a 2500 to 3000-word (not including figures, tables, and references) report of a set of 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. 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 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 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.
- does not require a lot of background or 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 dedicated to Introduction, 10% to Discussion, and 80% to Methods and Results.
- 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 5-10 pieces of appropriate literature, going beyond the list of indicative readings in the course outline. Use the citation style included at the end of this outline.
- 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.
You will be marked based on the following criteria:
- Quality of the project
- Quality of writing
- Quality of references
- Conformity to instructions
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The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.
The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.
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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.
Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:
- Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
- Late submission permitted. 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.
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Human behavioural ecology; quantitative analyses; peoples and cultures of Southeast Asia and the Pacific
Dr Geoff Kushnick