STATS 240 : Design and Structured Data

Science

2020 Semester Two (1205) (15 POINTS)

Course Prescription

An introduction to research study design and the analysis of structured data. Blocking, randomisation, and replication in designed experiments. Clusters, stratification, and weighting in samples. Other examples of structured data.

Course Overview

STATS 240 covers two of the most important types of statistical research study: the survey and the designed experiment. STATS 240 is recommended for anyone doing a major in Statistics, but is also useful for undergraduate students from other majors in Science, Engineering, and Commerce who are interested in sample surveys or designed experiments. The characteristics of a well-designed survey, as well as practical considerations and administrative issues are discussed. Different sampling methods (stratified, cluster, multistage) are introduced and their strengths and weaknesses explored. The proper analysis of data from surveys based on the sampling design and making valid inferences about a population using this analysis is emphasized. The underlying fundamental principles (replication, randomisation and blocking) of statistical experimental design are explained and their importance discussed. The concepts of block structure and treatment structure of an experiment are introduced. The characteristics and proper analysis (using the appropriate data model) of the most common types of designs (completely randomised, random complete block, balanced incomplete block, split plot) are explored in detail with an emphasis on making valid inferences about the system being studied.

STATS 240 has replaced STATS 340 which is no longer offered.

Course Requirements

Prerequisite: STATS 101 or 108 Restriction: STATS 340

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
Graduate Profile: Bachelor of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Communicate effectively the findings from the analysis of data from a designed experiment. (Capability 1, 2 and 4)
  2. Describe the three fundamental principles of experimental design and explain why each is important. (Capability 1 and 4)
  3. Analyse data from a designed experiment and interpret the results. (Capability 1, 2 and 4)
  4. Create graphs that effectively communicate the results of a statistical analysis. (Capability 1, 3 and 4)
  5. Identify, programme, and describe complex survey designs. (Capability 1, 2 and 4)
  6. Undertake, analyse and interpret survey data. (Capability 1, 2, 3 and 4)
  7. Explain the considerations when making decisions about sampling design. (Capability 1, 2 and 4)
  8. Describe the impact of survey conduct on data quality and the accuracy of results. (Capability 1, 2 and 4)
  9. Describe the principles underlying ethical research. (Capability 1, 2, 4 and 6)

Assessments

Assessment Type Percentage Classification
Final Exam 55% Individual Examination
Test 15% Individual Test
Assignments 30% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6 7 8 9
Final Exam
Test
Assignments

Learning Resources

Lecture notes are provided.

Special Requirements

None.

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 3 hours of lectures, a 1 hour tutorial, 2 hours of reading and thinking about the content and 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.

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.

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 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.

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 (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 06/07/2020 01:17 p.m.