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Overview

Course Prescription

Intended for anyone who will ever have to collect or make sense of data, either in their career or private life. Steps involved in conducting a statistical investigation are studied with the main emphasis being on data analysis and the background concepts necessary for successfully analysing data, extrapolating from patterns in data to more generally applicable conclusions and communicating results to others. Other topics include probability; confidence intervals, statistical significance, t-tests, and p-values; nonparametric methods; one-way analysis of variance, simple linear regression, correlation, tables of counts and the chi-square test.

Course Overview

An ability to gain insight from data enables organisations and individuals to inform their decisions, make predictions and generate new knowledge. Advances in technology allow us new ways of thinking and reasoning in the physical and social sciences, and finance. The purpose of this course is to introduce students to statistical investigation and analysis, and equip them with the skills and confidence needed to navigate the modern world of data. 

This is a core course in all majors/pathways for Statistics. It is also a supporting course for many other subjects (e.g. Psychology, Economics, Finance, Mathematics, Computer Science, Geography, Biology, Sociology,…).


The course covers some material similar to NCEA statistics but at a higher level and more advanced material is also covered. While some Year 13 statistics or mathematics is helpful, we do not assume or require that you have any formal background in statistics or mathematics. If you have a limited background in mathematics, you may want to consider STATS 100 as an alternate course or as preparation before taking this course.

Key Topics

  • Module 1: Modern data technologies and responsibilities (Datafication, Classification, Prediction, Randomisation)
  • Module 2: Making and evaluating claims or decisions based on data (Estimation, Quantification, Confirmation, Explanation)
  • Module 3: Designing and communicating about data (Variation, Distribution, Regression, Generalisation)

Workload Expectations

This course is a standard 15-point course and students are expected to spend 12.5 hours per week involved in each 15-point course that they are enrolled in. For this course, a typical weekly workload includes:

  • 3 hours of lectures
  • Regular drop-in help sessions
  • 5-6 hours of reading and thinking about the content
  • 4 hours of work on tasks, quizzes and/or test preparation (including up to 1 hour of optional drop-in help sessions).

Course Prerequisites, Corequisites and Restrictions

Restriction

Locations and Semesters Offered

LocationSemester
City
City
City

Teaching and Learning

Campus Experience

Lectures will be available as recordings. Other learning activities including drop-in help sessions will not be available as recordings.
The course will include live online events including lectures.
The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Taught courses use a learning and collaboration tool called Canvas to provide students with learning materials including 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.

Additional Information on Learning Resources

Access to a custom online coursebook is provided via Canvas. 

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.

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 course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

Other Information

Choosing your course:

  • If you are studying for a BCom, BProp, BPlan or BArch you should enrol in STATS 108.
  • If you are studying for a BSc, BA or other degree you should enrol in STATS 101.
  • If you have a limited background in mathematics, you may want to consider STATS 100 as an alternate course or as preparation before taking this course.

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 for potential plagiarism or other forms of academic misconduct, using computerised detection mechanisms.

Similarly, research students must meet the University’s expectations of good research practice. This requires:

  • Honesty - in all aspects of research work
  • Accountability - in the conduct of research
  • Professional courtesy and fairness – in working with others
  • Good stewardship – on behalf of others
  • Transparency – of research process and presentation of results
  • Clarity - communication to be understandable, explainable and accessible

For more information on the University’s expectations of academic integrity, please see the Academic Conduct section of the University policy hub.

Disclaimer

Elements of this outline may be subject to change. The latest information about taught courses is made available to enrolled students in Canvas.

Students may be asked to submit assessments digitally. The University reserves the right to conduct scheduled tests and examinations online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.


Assessment and Learning Outcomes

Additional Information on Assessment

A minimum of 45% is required in the exam to pass, in addition to a minimum of 50% in your overall mark.

Special Requirements

The online test will be held during the evening.

Course Learning Outcomes

CLO #OutcomeProgramme Capability Link
1
2
3
4
5
6

Assessments

Assessment TypeAssessment PercentageAssessment Classification

Assessment to CLO Mapping

Assessment Type123456

Student Feedback, Support and Charter

Student Feedback

Feedback on taught courses is gathered from students at the end of each semester 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. In addition, class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

Additional Information on Student Feedback

In response to student feedback, we have made numerous changes including:

  • Changed task marking to a feedback mark and a final mark. Students who engaged with all parts of the tasks and submitted on time got full marks.
  • Changing the due time of quizzes and tasks to 10pm.
  • Notes and interactive exercises are released well in advance of the lectures and any related assessment dates.
  • Lecture notes are being modified to make the connection between the learning outcomes, the lectures and the assessments more explicit.

Class representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Tuākana

Tuākana is a multi-faceted programme for Māori and Pacific students providing topic specific tutorials, one-on-one sessions, test and exam preparation and more. Explore your options at Tuakana Learning Communities.

Additional Information on Tuākana

Tuākana Statistics is the Māori and Pasifika community of learning in the Department of Statistics. We offer the following support to our Māori and Pasifika students: drop-in sessions for guidance with the quiz and task, one-to-one assistance on any aspect of the course, and study wānanga for the test and exam. For more information, contact Susan Wingfield (s.wingfield@auckland.ac.nz) or Heti Afimeimounga (h.afimeimounga@auckland.ac.nz).

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.

Wellbeing

We all go through tough times during the semester, or see our friends struggling. There is lots of help out there - please see the Support Services page for information on support services in the University and the wider community.

Special Circumstances

If your ability to complete assessed work 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. This should be done as soon as possible and no later than seven days after the affected test or exam date.

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.

Student Academic Complaints and Disputes

Students with concerns about teaching including how a course is delivered, the resources provided, or supervision arrangements, have the right to express their concerns and seek resolution. The university encourages informal resolution where possible, as this is quicker and less stressful. For information on the informal and formal complaints processes, please refer to the Student Academic Complaints Statute in the Student Policies and Guidelines section of the Policy Hub.