STATS 701 : Advanced SAS Programming


2020 Semester One (1203) (15 POINTS)

Course Prescription

A continuation of STATS 301, with more in-depth coverage of programming in the SAS language. Topics covered will include advanced use of the SAS language, advanced data step programming, macros, input and output, connectivity to other software platforms, SAS SQL.

Course Overview

One of the key purposes of STATS 701 is to advance your knowledge of SAS software for the purposes of data merging, transformation and re-shaping. We will use SAS as a programming language, and some more advanced features of SAS programming (arrays, macros, SQL etc) will be covered. STATS 701 is designed to be a practical course in the use of SAS in industries such as Medicine, Market Research and Finance. Students are expected to have a basic grounding in Statistics, and should have completed STATS 301 as a minimum requirement. To date all the data you have seen has usually been given to you in a form ready for exploration and modelling. This is rarely the case in most day to day projects in industry. Here, the emphasis will be on getting data from a 'raw and messy' form into a state ready for the data analysis techniques that you have learned at undergraduate level. The emphasis in 701 will be very heavily on the practicalities of data handling and reporting, and there will be very little new material on statistical inference; from time to time we will be using much larger data sets than you have previously encountered.

Course Requirements

Prerequisite: STATS 301

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: Master of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Create data structures in a form that is appropriate to specific analyses
  2. Demonstrate capability in SAS programming to create and re-structure datasets that have been output from various SAS analytic procedures in a form appropriate for reporting (Capability 1, 3 and 4)
  3. Apply SAS graphical capabilities to a variety of designed graphical outputs (Capability 3 and 4)
  4. Analyse data in a variety of standard analytic situations, such as analysis of variance and covariance, regression analyses, time series analyses, logistic and proportional hazards regression. (Capability 1, 2, 3 and 4)


Assessment Type Percentage Classification
Workshops 40% Group Coursework
Assignments 30% Individual Coursework
Test 20% Individual Test
Professional Development 10% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4
Professional Development

Key Topics

Data step capabilities
Using the SAS ODS system - data files and graphics
Creating and using Macros
Using the SQL capabilities of SAS
Statistical techniques: Anova, Ancova, Time Series, Datamining, Logistic regression, Cox Proportional Hazards Regression
Using the reporting facilities of SAS

Learning Resources

No required text, but the introductory SAS text, The Little SAS book: A Primer, by Delwiche and Slaughter, which was used for STATS 301 is highly recommended.

Special Requirements

You must obtain at least 30% out of the 60% available in the assignments and test, and at least 15% in the weekly workshops to pass. A further 5% on top of these minimum criteria is needed from the "professional development" assessment to achieve the 50% needed to pass, based on the lecturer’s assessment of the student’s professional behaviour: class contribution, ability to work alone, and in small teams.

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 2 hours of lectures, a 2 hour tutorial, perhaps 2 hours of reading and thinking about the content and up to a further 4 hours of work on assignments and/or test preparation.

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.

Data files will be provided via CANVAS, or in some cases, students may be required to access data from internet sources.
Hints and guideline SAS code will be given for workshops and assignments.
Since there are many approaches to the coding for any specific problem, in general "model answers" will not be provided.


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.

Because many of the workshops and assignments have emerged from "real-world" consulting assignments, the specifications for these are somewhat looser than students may be accustomed to - this can lead to some level of discomfort, but is closer to real statistical practice, and students are invited to go beyond the brief where they believe they can add value.

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 01:13 p.m.