An Overview of Causal Inference and its Applications in Health-care and Finance using methods such as Bayesian Networks and Granger’s Causality
Gayatri Bangar, Sameer Mahajan, Vedang Naik, Rohit Sahoo · Journal of Emerging Technologies and Innovative Research · 2021
Causal Inference is a discipline that involves discovering the causal connections between various statistically related quantities. Unlike Statistical Analysis, which focuses on answering the question of “what?” Causal inference is concerned with answering the question of “why?”. Causal inference has significant applications in the fields of Health-care, Finance, etc. In this paper, we will be exploring some fundamental concepts in Causal Inference and how it is used in the field of medicine and finance. In Section I we will be providing an introduction to the concept of causality, moving to the Section II we will be looking at various aspects of causal inference. Following that we will see basic concepts of causal model. In section IV, V we will be discussing the implementation of causal in the field of health-care and finance.