TFCSTATS 92F : Data Analytics


2021 Semester Two (1215) (15 POINTS)

Course Prescription

Provides an introduction to statistics for anyone who will ever have to collect, analyse or interpret data, either in their career or private life. Statistical skills will be developed through Exploratory Data Analysis of real data using appropriate technology and statistical techniques. An important aspect of the course will involve communicating results to others in verbal or written form.

Course Overview

This is a one-semester course designed for students who at present lack the   necessary   background   for   tertiary   courses   in   statistics.  Some knowledge  of  basic  material  found  in  Maths  91F  is  expected.  The  course focuses  on  the  development  of  statistical  skills  and  concepts  using appropriate  software  tools.  The  aim  is  to  build  confidence  and  foster enjoyment in statistics, as well as to provide a preparation for further study, such as STATS 10X. Some of the material will overlap with content covered in STATS 100. The focus will be on evaluation and interpretation of statistics produced by technology rather than calculation of specific statistics.

Course Requirements

No pre-requisites or restrictions

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 6: Social and Environmental Responsibilities

Learning Outcomes

By the end of this course, students will be able to:
  1. Analyse and evaluate media reports about experiments, observational studies, polls and surveys (Capability 1, 2, 4 and 6)
  2. Develop and demonstrate statistical software skills using spreadsheets, CODAP and iNZight (Capability 1, 2 and 3)
  3. Develop and demonstrate good techniques for exploratory data analysis using appropriate software tools (Capability 1, 2 and 3)
  4. Evaluate linear relationships and develop linear models using regression techniques (Capability 1, 2, 3 and 6)
  5. Describe and explain the difference between correlation and causation (Capability 1 and 2)
  6. Discover and develop an understanding of time series using appropriate software tools (Capability 1, 2, 4 and 6)


Assessment Type Percentage Classification
Final Exam 40% Individual Examination
Quizzes 8% Individual Coursework
Tests 12% Individual Test
Assignments 12% Individual Coursework
Coursework 12% Group Coursework
Portfolio 16% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6
Final Exam
Students must achieve 35% or higher in the final exam in order to pass this course.


The Department of Statistics has a team of eight Tuākana tutors covering undergraduate Statistics courses. For details of supported courses and online session times, visit our Canvas page. If you do not have access to our Canvas page or need information regarding online support please contact our programme coordinator, Susan, Email:

Key Topics

Four main units of work.
Evaluation of statistical reports
Introduction to software skills
Exploratory data analysis
Regression and Correlation

Special Requirements

No special requirements.

Workload Expectations

This course is a standard 15 point course and students are expected to spend 150 hours per semester in each 15 point course that they are enrolled in.

For this course, you can expect 2 hours of lectures, 2 hours of tutorials, 2.5 hours of online activity, 3 hours reading and thinking about the content and 3 hours of work on assignments and/or test preparation per week. In addition there will be up to 4 optional help sessions that students may attend.

Delivery Mode

Campus Experience

Attendance is expected at scheduled activities including lectures, tutorials and all assessments.
Lectures will be available as recordings, provided the timetabled room has recording facilities. Other learning activities including tutorials will not be available as recordings.
The course will not include live online events.
Attendance on campus is required for the tests and the final exam.
The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course book, worksheets, powerpoint lecture slides, podcasts are all provided.
If students want additional information they are directed to "Chance Encounters: A first course in data analysis and inference" by Wild & Seber

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.

All student feedback is carefully evaluated and modifications to the course will be implemented as a result of constructive feedback.

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.


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

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

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.

Students will be expected to have access to a device and a good internet connection in the event of learning returning to an online environment. Any student who does not have access to these things should notify the University as soon as possible.
At Level 1, this course will be delivered in person on the city campus.
At Levels 2 & 3, you will not be required to attend in person. All teaching and assessment will be offered 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


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 26/01/2021 09:21 a.m.