This course is designed to provide the student with an introduction to the principles and methods by which research projects in biological anthropology are devised and executed. It will deal with the issues of finding a topic to research, defining its scope and limitations, developing a research bibliography, elaborating a research design, defining and collecting relevant data, methods of data analysis, data presentation and hypothesis testing. The main aim of this course is to prepare students considering Honours in Biological Anthropology for the thesis component of the Honours year, though it does not require a commitment to Honours and is open to other students who fulfil the prerequisites.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

1. understand and explain the basic concepts that underlie quantitative analysis that is informative, replicable, and amenable to meta-analysis;
2. use statistical software to carry out estimation analysis that is informative, replicable, and amenable to meta-analysis;
3. ask and answer meaningful research questions; and
4. develop a robust research proposal by incorporating statistical thinking at every stage of the process.

Research-Led Teaching

This course is is guided by research-led teaching. It will draw on research on statistical methods and statistical cognition discussed in the book Understanding the New Statistics: Effect Sizes, Confidence Intervals, and Meta-Analysis. The students will get the opportunity to hear a guest lecture from the book's author (Professor Geoff Cumming), as well as Professor Nicole Lazar (Penn State University; one of the proponents of the statistical reform). Both speakers will draw heavily on their careers in the area of statistical research and collaboration.

Field Trips

None

Additional Course Costs

None

Required Resources

You will need access to a computer during tutorials (particularly in Weeks 2, 4, 6, 7). The convener will provide instructions on how to download the relevant software: R and esci in jamovi.

Recommended Resources

Whether you are on campus or studying online, there are a variety of online platforms you will use to participate in your study program. These could include videos for lectures and other instruction, two-way video conferencing for interactive learning, email and other messaging tools for communication, interactive web apps for formative and collaborative activities, print and/or photo/scan for handwritten work and drawings, and home-based assessment.

ANU outlines recommended student system requirements to ensure you are able to participate fully in your learning. Other information is also available about the various Learning Platforms you may use.

Staff Feedback

Students will be given feedback in the following forms in this course:

• written comments
• verbal comments
• discussion with class representative

Student Feedback

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). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Lecture: Overview of the course; Introduction to statistical thinkingTutorial: class discussion and collaborative problem solving	Assignment 1: completion of journal entry (300 words); marked on evidence of self-reflection, not content
2	Lecture: Research fundamentals, and avoiding falling into trapsTutorial: hands-on introduction to R	Assignment 2: completion of a guided problem-set
3	Guest lecturers (Prof Geoff Cumming; Prof Nicole Lazar): The importance of a statistical reformTutorial: no tutorial this week	Assignment 3: mini-essay (400 words), reflecting on the main messages from Prof Cumming and Prof Lazar's lectures
4	Lecture: From Null Hypothesis testing to Confidence Intervals and Effect SizesTutorial: hands-on introduction to esci in jamovi	Assignment 4: mini-report (3 figures produced in jamovi accompanied by 100 word descriptions of each figure)
5	Lecture: ReplicationTutorial: class discussion and collaborative problem solving	Assignment 5: mini-essay (400 words) comparing statistical approaches of published studies and suggesting changes
6	Lecture: Precision for planningTutorial: class discussion and collaborative problem solving	Assignment 6: outline of your plan for the main class project (research proposal) (300 words; combination of bullet points and paragraphs); full proposal due Nov 7th
7	Lecture: Meta-analysis (small- and large-scale)Tutorial: hands-on activities (in jamovi) on carrying out meta-analyses	Assignment 7: mini-report (1 forest plot produced in jamovi, accompanied by 200 word description)
8	Lecture: Cohen's d, Statistical powerTutorial: class discussion and interactive problem solving (in jamovi)	Assignment 8: completion of a guided problem-set
9	Lecture: no lecture (public holiday)Tutorial: class discussion and collaborative problem solving (in jamovi)	Assignment 9: completion of a guided problem-set
10	Lecture: Correlations and proportionsTutorial: class discussion and collaborative problem solving	Assignment 10: mini-research proposal on risk literacy (300 words)
11	Lecture: More complex designsTutorial: class discussion and collaborative problem solving	Assignment 11: design a meme on one of the course topics (meme + 200 word description)
12	Lecture: Course recapTutorial: oral presentations of memes (Assignment 11)	Assignment 12: main class project (research proposal) due midnight on November 7rd (1500 words)

Tutorial Registration

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities/tutorials so they can better plan their time. Find out more on the Timetable webpage.

Assessment Summary

Assessment task	Value	Due Date	Learning Outcomes
Journal entry on prior knowledge of statistics	7 %	04/08/2023	1
Research fundamentals: guided problem set	7 %	11/08/2023	1,3,4
Reflective essay on the importance of the statistical reform	7 %	18/08/2023	1,2,3
Confidence intervals: mini-report	7 %	25/08/2023	1,2,3
Replication: mini critical essay	7 %	01/09/2023	1,3,4
Main class project: research proposal	7 %	08/09/2023	1,2,3,4
Meta-analyses: mini-report	7 %	29/09/2023	1,2,3
Cohen's d: guided problem set	7 %	06/10/2023	1,2,3,4
Statistical power: guided problem set	7 %	13/10/2023	1,2,3,4
Correlations and proportions: mini research proposal	7 %	20/10/2023	1,3,4
Understanding Open Science and New Statistics: a meme	7 %	27/10/2023	1,3
Main class project: research proposal	30 %	07/11/2023	1,2,3,4

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

• Academic Integrity Policy and Procedure
• Student Assessment (Coursework) Policy and Procedure
• Special Assessment Consideration Guideline and General Information 
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure
• Code of practice for teaching and learning

Assessment Requirements

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 Skills website. 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.

Participation

Participation at tutorials is required.

Lectures should be listened to and the embedded questions answered before attending tutorials.

Examination(s)

None.

Assessment Task 1

Journal entry on prior knowledge of statistics

For submission: a 300 word journal entry reflecting on your prior engagement with statistics. The assignment will be graded based on evidence of self-reflection, and not based on content.

Assignment expectations will be provided on Wattle and during the Week 1 lecture.

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 2

Research fundamentals: guided problem set

For submission: answers to short-answer questions (students will learn how to answer similar questions during the week's lecture & tutorial).

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 2 tutorial.

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 3

Reflective essay on the importance of the statistical reform

For submission: a 400 word essay, reflecting on the main messages from Prof Cumming's and Prof Lazar's guest lectures.

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 2 tutorial.

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 4

Confidence intervals: mini-report

For submission: 3 figures produced using esci in jamovi accompanied by 100 word descriptions of each figure.

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 4 tutorial.

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 5

Replication: mini critical essay

For submission: a 400 word essay on evaluating statistical approaches from the published literature and suggesting alternate approaches.

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 5 tutorial.

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 6

Main class project: research proposal

For submission: a 300 word outline of your plan for writing your main research proposal for the course; combination of bullet points and full-paragraphs allowed; include appropriate citations of academic articles and online resources (citations do not count towards word count)

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 9 tutorial. 

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 7

Meta-analyses: mini-report

For submission: 1 forest plot produced using esci in jamovi, accompanied by a 200 word description of the research findings.

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 8 tutorial.

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 8

Cohen's d: guided problem set

For submission: answers to short-answer questions (students will learn how to answer similar questions during the week's lecture & tutorial).

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 6 tutorial.

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 9

Statistical power: guided problem set

For submission: answers to short-answer questions (students will learn how to answer similar questions during the week's lecture & tutorial).

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 7 tutorial.

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 10

Correlations and proportions: mini research proposal

For submission: a 300 word essay describing a hypothetical research plan for studying risk literacy.

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 9 tutorial. 

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 11

Understanding Open Science and New Statistics: a meme

For submission: a meme + 200 word description on a topic assigned during Week 11 tutorial.

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 11 tutorial. 

Assessments 1–11 have an equal weighting of 7%, and students will have the option to drop the lowest grade.

Assessment Task 12

Main class project: research proposal

For submission: a 1,500 word essay (covering background research, hypothesis and description of variables, materials & methods, expected findings); include appropriate citations of academic articles (citations do not count towards word count).

Assignment expectations and grading rubric will be provided through Wattle and explained in Week 1, 9, 12.

Deadline: midnight on November 7th

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

 

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

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) submission must be through Turnitin. Tutorial participation and take-home tests will use a Wattle submission portal that is not Turnitin. You will need to scan your take-home tests -- using a proper scanner (available on campus) or a scanning app on your phone -- to submit the tests.

Hardcopy Submission

Hardcopy submissions are not accepted in this course.

Late Submission

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.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted 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.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Access and inclusion for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents undergraduate and ANU College students
• PARSA supports and represents postgraduate and research students