How Misuse of Statistics Can Spread Misinformation: A Study of Misrepresentation of COVID-19 Data

TL;DR

This paper examines how improper statistical representation of COVID-19 data can lead to misinformation, emphasizing the importance of correct visualization and adherence to guidelines, especially in the Indian context.

Contribution

It highlights the risks of misrepresenting epidemiological data and underscores the need for proper statistical techniques and visualization methods to prevent misinformation.

Findings

Misuse of statistics can distort pandemic understanding

Incorrect data visualization leads to misinformation

Proper guidelines improve data interpretation

Abstract

This paper investigates various ways in which a pandemic such as the novel coronavirus, could be predicted using different mathematical models. It also studies the various ways in which these models could be depicted using various visualization techniques. This paper aims to present various statistical techniques suggested by the Centres for Disease Control and Prevention in order to represent the epidemiological data. The main focus of this paper is to analyse how epidemiological data or contagious diseases are theorized using any available information and later may be presented wrongly by not following the guidelines, leading to inaccurate representation and interpretations of the current scenario of the pandemic; with a special reference to the Indian Subcontinent.