STATS 747 : Statistical Methods in Marketing

Science

2021 Semester Two (1215) (15 POINTS)

Course Prescription

Stochastic models of brand choice, applications of General Linear Models in marketing, conjoint analysis, advertising media models and marketing response models.

Course Overview

The aim of this course to introduce students to the work demands typically encountered by  quantitative  researchers in market research and to learn how best to communicate these results  to clients, and fellow researcher,s who do not  have knowledge of these techniques.  Clients understand there markets but, typically, do no understand how to frame their questions  with the techniques that students have learnt at undergraduate and post-graduate level. There is a deep need for graduates who can  work as interpreters  between both of these 'worlds'. This course  addresses these needs. Students who master these interpretative skills do very well in commercial environments. Students are taught how to manage  projects  in the 'time poor' environments they may encounter when employed. This course is based on the experiences of the lecturer  in having worked as a quantitative market researcher to academia -  who maintains ongoing links with this industry. Students who succeed in this course are given skills that allow them to flourish upon employment after graduating. 

Course Requirements

Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, 210, 707

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Capability 5: Independence and Integrity
Capability 6: Social and Environmental Responsibilities
Graduate Profile: Master of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Understand and critically evaluate what the client is asking and how it can be famed using the statistical techniques learnt to date. (Capability 2, 3 and 4)
  2. Demonstrate an appropriate modelling procedure, outlining how this is driven by the aims of the clients questions. (Capability 1, 4 and 5)
  3. Understand and apply the types of statistical and/or data manipulation packages that can be used most effectively for the client/question of interest. (Capability 3)
  4. Understand and explain how to interpret the output from the computer program/packages. (Capability 3)
  5. Develop their own bespoke-code to solve novel problems (Capability 2, 3 and 6)
  6. Communicate to non-quantitative audiences in a meaningful and illuminating way. (Capability 2 and 4)
  7. Be able to manage their time efficiently. (Capability 5)

Assessments

Assessment Type Percentage Classification
Project part 2 20% Individual Coursework
Project part 1 30% Individual Coursework
Assignments 50% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6 7
Project part 2
Project part 1
Assignments

Special Requirements

Student must attend all classes (compulsory unless they have a good excuse)  and engage in the class discussion and tutorial meetings. they must show the ability to undertake self-directed research. If we have covid restrictions  then  lectures are still compulsory as zoom meetings.

Workload Expectations

This course is a standard 15 point course and students are expected to spend 150 hours per semester involved in each 15 point course that they are enrolled in. For this course you can expect 12 hours of lectures, a 36 hours of instructed  tutorial, 102 hours of reading and thinking about the content and hours of work on assignments and/or project preparation.


Delivery Mode

Campus Experience

Attendance is required/expected at scheduled activities including  lectures and laboratories to complete/receive credit for components of the course if there are no covid restrictions.
Lectures will be available as recordings only if we have covid restrictions. Other learning activities including labs will not be available as recordings.
The course may include live online events including group discussions.
Attendance on campus is not required for the test.
The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course notes provided. Using online resources code encouraged.

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course 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.

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

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.

Copyright

The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

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

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.

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.

Level 1: Delivered normally as specified in delivery mode 
Level 2: You will not be required to attend in person. All teaching and assessment will have a remote option. 
Level 3 / 4: All teaching activities and assessments are delivered remotely.

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 28/01/2021 11:49 a.m.