The amount of data generated as a by-product in society is growing fast including data from satellites, sensors, transactions, social media and smartphones, just to name a few. Such data are often referred to as "big data", and can be used to create value in different areas such as health and crime prevention, commerce and fraud detection. Big Data are often used for prediction and classification tasks. Both of which can be tackled with machine learning techniques. In this course we explore how Big Data concepts, processes and methods can be used within the context of Survey Research. Throughout this course we will illustrate key concepts using specific survey research examples including tailored survey designs and nonresponse adjustments and evaluation.
This course will offer participants:
Grading will be based on:
We recommend good understanding of the material typically taught in undergraduate statistics courses and some familiarity with regression techniques. Knowledge about survey data collection at the level provided in the IPSDS course Fundamentals of Survey and Data Science.
We recommend familiarity with the software package R