Managers today need to better understand cause and effect in a organisations where data plays an important role in decision-making. While machine learning and AI tools can help with identifying relationships in data, such standard tools often do not detect cause and effect relationships in the data. This creates a shortcoming for managers and strategists where these algorithms may not allow to answer important questions in business analytics and decision making regarding “what is the effect of X on Y?” or “did X cause Y to change?”. Many prominent firms such as Google, Uber, Zalando, McKinsey and Spotify are investing in their causal data science capabilities.
This module will provide an introduction to the topic of causal inference with a focus on machine learning and AI based problems in business. In this module, students will conceptually learn how to apply causal inference for data and evidence driven decision making, at the intersection of data science and management strategy. Students will be exposed to various examples to apply concepts from causal analyses learnt in the module. The module will first introduce students to the world of causal inference, and cover standard tools that are used in empirical research, such as instrumental variables, regression discontinuity designs, difference-in-differences. The module will also include case studies that cover machine learning and AI based problems in business decisions.
As the module will cover these topics conceptually, students do not need a particular background to take this class. However, some concepts such as conditional means, variances, hypothesis testing and regression will be covered at the beginning of the module. In-class lectures feature case studies and examples of causal inference research designs.
The objective is that the student after the module possesses the necessary knowledge on:
The objective is that the student after the module possesses the necessary skills in:
The objective is that the student after the module possesses the necessary competences in:
For information see § 17.
|Name of exam||Causal Design for Decision Making in Business|
|Type of exam|
Written examIndividual examination.
|Assessment||7-point grading scale|
|Type of grading||Internal examination|
|Criteria of assessment||The criteria of assessment are stated in the Examination Policies and Procedures|
|Danish title||Kausal design for beslutningstagning i erhverv|
|Language of instruction||English|
|Location of the lecture||Campus Aalborg|
|Responsible for the module|
|Study Board||Study Board of Economics and Business Administration|
|Department||AAU Business School|
|Faculty||Faculty of Social Sciences and Humanities|