ANTHRO 309 : Quantitative Methods in Anthropology

Arts

2021 Semester One (1213) (15 POINTS)

Course Prescription

Introduces analytical approaches to anthropological data, emphasising application of statistical principles to research design. Strongly recommended for all students of anthropology considering postgraduate study. Concepts and topics include: variable scales, operational definitions, sampling, choosing appropriate statistical tests, error, measures of central tendency and dispersion, accuracy, bias and validity. This course assumes only a limited mathematical background.

Course Overview

This course is designed as an introduction to quantitative methods used in anthropology. It assumes no statistical or computer background and requires only basic mathematics. The emphasis will be on quantitative analysis as an anthropological research tool, not on probability or statistical theory, although these will be discussed. Students will be taught the basic use of  R programming language, and some introduction to Excel will also be included. Computer Labs will be conducted in the Arts Faculty Computer Labs. Students will have full access to the computing facilities in the Arts Labs. The syllabus and the links it contains to labs and readings will be available through CANVAS.

Course Requirements

Prerequisite: ANTHRO 200 or 201 or 203 or 120 points passed Restriction: SOCSCRES 300

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Graduate Profile: Bachelor of Arts

Learning Outcomes

By the end of this course, students will be able to:
  1. Teach the student to read and understand statistical applications in anthropology (Capability 1.1, 1.2, 1.3, 2.1 and 4.2)
  2. Teach the student to design and conduct basic quantitative analysis (Capability 1.1, 1.2, 1.3, 2.1, 2.3, 4.1 and 4.2)
  3. Introduce the student to the range of quantitative techniques useful in anthropological research (Capability 1.1, 1.2, 1.3, 2.1, 2.2, 3.1 and 4.1)

Assessments

Assessment Type Percentage Classification
Laboratories 30% Individual Coursework
Tests 40% Individual Coursework
Research Project 30% Individual Coursework

Next offered

Semester 1, 2021

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course, you can expect 3 hours of lectures, a 1 hour lab, 2 hours of reading and thinking about the content and 4 hours of work on assignments and/or test preparation.

Delivery Mode

Campus Experience

Attendance is required at scheduled activities including labs to complete components of the course.
Lectures will be available as recordings. Other learning activities including labs will not be available as recordings.
Attendance on campus is require for the test.
The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

  1. Quantitative Analysis in Archaeology by VanPool and Leonard. This will be available through Talis.

Student Feedback

At the end of every semester students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback and respond with summaries and actions.

Your feedback helps teachers to improve the course and its delivery for future students.

Class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

Feedback from the last time I taught the course. I will use this feedback to improve the 2021, semester 1, version (lecturer comments in curly brackets {}):
 What aspects of the course were most helpful for your learning:
  • The lectures help show which parts of the course material are important and helps [to] explain them.
  • The lecture slides, going over the readings in class and the moderate pace of learning content is great.
  • Lecturer is really good at organizing content .
  • ...lecturing and explanations in class as well as labs .
  • Teaching style, availability of lecturer and tutor .
  • Readings, lectures (readings are really clear and lectures give good simple explanations).
  • Enjoy the labs because it puts the theory into practice.
  • The application of stats to anthropology casework.
What changes to the course would you most like to see? 
  • more refreshers each lecture to revise the content learnt last time before going into the new lecture but otherwise everything is fantastic - have already found this very useful for other classes and am starting to see connections 
  • Record lectures. Summary of the lecture at the end of the slides. I was sick for a couple of weeks in last semester and have found it difficult to catch up as some slides are hard to understand without [lecturer] explanations {Lecturer note: lectures are now recorded}.
  • More feedback in class about the labs/assignments {Lecturer note: I will work towards this}
  • Possibly less weighted marks on the labs (for next time around). {Lecturer note: lab weighting is the same.}
  • To have full notes of worked out examples - so you know what different situations apply to what hypothesis, and what test statistic to use. At the moment on the lecture slides and in lectures, it isn't always put plainly what to use when. {Lecturer note: while I understand the concern, it is not possible to supply a full list of  "what to use when", as each situation is unique. My goal is to have students understand the principles, so they can creatively apply valid quantitative tools in standard and unique situations.}

Digital Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Well-being always comes first
We all go through tough times during the semester, or see our friends struggling. There is lots of help out there - for more information, look at this Canvas page https://canvas.auckland.ac.nz/courses/33894, which has links to various support services in the University and the wider community.

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and your assessment is fair, and not compromised. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator, and if disruption occurs you should refer to the University Website for information about how to proceed.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.

Published on 22/12/2020 04:44 p.m.