The Social Research Centre and the Statistical Society of Australia (SSA) are very proud to offer statistical training from the International Program in Survey and Data Science (IPSDS), a joint program of the University of Mannheim and the Joint Program in Survey Methodology at the University of Maryland.
Places are limited, please register early to take advantage of early bird discounts and secure a place.
Topics:
1. Overview of Big Data; Working with Big Data, Classical Statistical Approaches vs. Statistical Machine Learning
2. Model Evaluation/Validation, K-Means Clustering
3. Nearest Neighbors, CARTS
4. Random Forests
Timeframe:
August 26 – September 16, 2025. Weekly Meetings taking place Tuesdays, 9:30 - 10:30 am AEST.
Course Objectives
This course covers… ▪ an overview of key Big Data terminology and concepts ▪ an introduction to common data generating processes ▪ a discussion of some primary issues with linking Big Data with Survey Data ▪ issues of coverage and measurement errors within the Big Data context ▪ inference versus prediction ▪ general concepts from machine learning including signal detection and information extraction ▪ potential pitfalls for inference from Big Data ▪ key analytic techniques (e.g. classification trees, random forests, conditional forests) to process Big Data using R with example code provided
Your instructor: Prof. Trent Buskirk
Current positions:
▪ Novak Family Professor of Data Science and Chair of the Applied Statistics and Operations Research Department at Bowling Green State University
▪ Adjunct Research Professor at the University of Michigan
Dr. Buskirk is a Fellow of the American Statistical Association. His research includes the areas of Mobile and Smartphone Survey Designs, methods for calibrating and weighting nonprobability samples, and the use of big data and machine learning methods for health, social and survey science design and analysis. His research has been published in leading journals such as Cancer, Social Science Computer Review, Journal of Official Statistics, and the Journal of Survey Statistics and Methodology.
Prerequisites
No prerequisites.
We recommend good understanding of the material typically taught in undergraduate statistics courses and some familiarity with regression techniques. While not a prerequisite, familiarity with the R software package (base R or R using Rstudio) is strongly encouraged.
Grading will be based on:
▪ 4 online quizzes (worth 5% each)
▪ Participation in discussion during the weekly online meetings and submission of questions to the weekly discussion forums demonstrating understanding of the required readings and video lectures (20% of grade).
▪ 3 homework assignments (worth 20% each)
Early Bird Deadline
Please book before 30 June.2025 to take advantage of the Early Bird Deadline.
Prices includes GST.
Disclaimer
Participants will receive access data for the online course, in particular to any learning platform that may be used. The rights of use connected to the access data are personally assigned to the participant. Passing on the access data is not allowed. Also, the temporary transfer to third parties is not permitted.
The right to use the transmitted access data, in particular with regard to any materials or video recordings provided, can only be exercised up to a maximum of 2 months after the program end. After expiration of this 2-months period, the access data will be deleted by Mannheim Business School (MBS). Before the expiration of this period, the participant may view the respective recorded course as often as desired and without time restriction.
If we have reasons to believe that the participant is abusing the right of use granted to him or that there is a violation of the terms of use, MBS reserves the right to change the participant’s access data as well as to partially or completely block the access or to prohibit the further use of the digital content.
Group bookings
For group bookings, please email events@statsoc.org.au with the names, email addresses, and telephone numbers of the participants in the group.
Cancellation Policy
Occasionally courses have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen.
Cancellations received prior to two weeks before the event will be refunded, minus the Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20.
From then onward no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to events@statsoc.org.au.
For any questions, please email events@statsoc.org.au
@StatSocAus
