Which of the following is NOT a source of bias in data?

Exploratory Data Analysis (EDA) is a crucial practice in the data analysis process that aims to summarize the main characteristics of the data, often using visual methods. It allows researchers to gain insights, identify patterns, and uncover anomalies within the dataset. By employing various statistical tools and visualization techniques, EDA helps to guide further analysis and ensures that the data is understood before more formal analysis is conducted.

Unlike the other options listed, which can introduce biases and distortions in data, EDA is a methodological approach intended to improve data quality and interpretation. Misleading questions can skew responses in surveys, forged data creates an entirely false representation of reality, and data entry errors can lead to inaccuracies. In contrast, EDA focuses on exploring and clarifying the data rather than introducing bias, making it an essential and impartial part of the research process.