STATS 220 : Data Technologies


2020 Semester One (1203) (15 POINTS)

Course Prescription

Explores the processes of data acquisition, data storage and data processing using current computer technologies. Students will gain experience with and understanding of the processes of data acquisition, storage, retrieval, manipulation, and management. Students will also gain experience with and understanding of the computer technologies that perform these processes.

Course Overview

This course introduces a variety of computer technologies relevant to storing, managing, and processing data. The course has two aims: to teach software tools specific to the handling of data, and to teach and build confidence with general concepts of computer languages and file formats. It is useful for students with interests in applying statistics in business or research environments. Lectures will be reinforced with weekly lab work. Topics studied include: How to write computer code; publishing data on the World Wide Web (HTML); data description and semantic markup (XML); data storage (file formats, spreadsheets, databases); data management and summary (database queries, SQL); R programming and data manipulation.

Course Requirements

Prerequisite: 15 points at Stage I in Computer Science or Statistics

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
Graduate Profile: Bachelor of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Write computer code. (Capability 1 and 2)
  2. Publish data on World Wide Web. (Capability 4)
  3. Understand the concepts underlying data description and semantic markup. (Capability 4)
  4. Understand and utilise data storage techniques. (Capability 4)
  5. Manage and summarise data effectively. (Capability 2, 3 and 5)
  6. Program in R. Understand how and when data manipulation can be beneficial. (Capability 1 and 2)


Assessment Type Percentage Classification
Assignments 20% Individual Coursework
Labs 10% Individual Coursework
Exam 50% Individual Examination
Midterm Test 20% Individual Test
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6
Midterm Test
You must obtain at least 50% overall and at least 50% in final exam to pass.
Plussage applies to the test. If it would make your overall mark higher, the test will count for 0% and the exam 70%.

Learning Resources

The course book is "Introduction to Data Technologies" by Paul Murrell and is available online at However, materials given out in class are sufficient to learn the material, and are more frequently updated.

Special Requirements

Labs are marked and count towards your final grade but attendance is not mandatory. You only need to attend the lab session if you need help. Many students are able to complete the questions without attending the lab sessions.

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 24 hours of lectures, 10 one-hour lab sessions, 15 hours of work on assignments, and 71 hours of combined reading, practising the material, and revising for tests and exams.

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.


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.

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 at

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.

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.

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 20/12/2019 01:18 p.m.