# STATS 740 : Sample Surveys

## Science

### Course Prescription

The design, management and analysis of sample surveys. Topics such as the following are studied. Types of Survey. Revision of statistical aspects of sampling. Preparing surveys. Research entry: problem selection, sponsorship and collaboration. Research design: methodology and data collection; Issues of sample design and sample selection. Conducting surveys: Questionnaires and questions; Non-sampling issues; Project management; Maintaining data quality. Concluding surveys: Analysis; Dissemination.

### Course Overview

STATS 740 provides an introduction to design and analysis of sample surveys. The first part of the course focuses on the design of surveys, with examples from recent or undergoing surveys. We will define sampling frames, target populations, different types of error, sampling error and sampling designs. We will briefly introduce different sampling designs such as simple random sampling, stratified, clustered, multistage, and pps (probability proportional to size). The second part of the course involves the analysis of data that arises from sample surveys. This part is more mathematical and includes formal definitions of sampling designs, as well as formal mathematical proofs. We will study estimators of totals, ratios and regression coefficients. We will also consider post-design techniques such as post stratification, the regression estimator and calibration estimator. This course is designed for students that are interested in learning how to design and analyse surveys,   including   sampling theory and software.    Each week has a 1-hour R tutorial and a 2-hour lecture.

### Course Requirements

Prerequisite: 15 points from STATS 340, 741 and 15 points from STATS 310, 732

### Capabilities Developed in this Course

 Capability 1: Disciplinary Knowledge and Practice Capability 2: Critical Thinking Capability 3: Solution Seeking

### Learning Outcomes

By the end of this course, students will be able to:
1. Explain and apply different probabilistic sampling designs (Capability 1)
2. Apply survey methods to estimate totals, means and regression coefficients under complex survey designs. (Capability 1)
3. Recognise and interpret feasible and useful sampling designs for different survey scenarios. (Capability 1)
4. Use and apply statistical software for the analyses of complex surveys. (Capability 1 and 3)
5. Describe methods to enhance analyses of existing sampling surveys using readily-available information. (Capability 2 and 3)

### Assessments

Assessment Type Percentage Classification
Assignments 40% Individual Coursework
Final Exam 60% Individual Examination
1 2 3 4 5
Assignments
Final Exam

### Learning Resources

Books (available from the UoA library)

R. Groves and et.al. Survey Methodology. Second edition, 2009.

T. Lumley. Complex Surveys. John Wiley & Sons, Inc., feb 2010. doi: 10.1002/9780470580066. URL https://doi.org/10.1002/ (Links to an external site.)

C. E. Sarndal, B. Swensson, and J. Wretman. Model Assisted Survey Sampling. Springer Series in Statistics, 1992.

L. A. Aday. Designing and conducting health surveys : a comprehensive guide. Jossey–Bass ; John Wiley, San Francisco, Calif. : Chichester, 3rd ed.. edition, 2006. ISBN 0787975605.

Software:
R packages:  survey  & sampling

### Special Requirements

NA

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 week, a 1 hour tutorial a week, 3 hours of reading and thinking about the content and 4 hours of work on assignments per week and/or test preparation.

### Other Information

Students DO NOT need to purchase any of the books. These are available from the UoA library

### 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.

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 20/07/2020 10:36 a.m.