Question

Define and explain the following types of Biases: Recall Bias, Survivor Bias

Hint:

\textbf{Remember:} Recall Bias → Memory errors. Survivor Bias → Ignoring failures.

Answer 1

Concept: Bias refers to systematic errors in data collection or analysis that lead to incorrect conclusions. Understanding different types of bias is important for accurate data interpretation.
1. Recall Bias: Definition: Recall Bias occurs when participants do not remember past events accurately, leading to incorrect or incomplete data. Explanation:

Common in surveys, interviews, and retrospective studies.
People may forget details or unintentionally distort memories.
This results in unreliable self-reported data.
Example: In a health survey, participants may not accurately remember how often they exercised or what they ate last year, leading to inaccurate data.
2. Survivor Bias: Definition: Survivor Bias occurs when analysis focuses only on successful or surviving cases while ignoring those that failed or were excluded. Explanation:

Leads to overly optimistic or misleading conclusions.
Happens when incomplete data is analyzed.
Important failures or missing cases are overlooked.
Example: Studying only successful startups to identify success factors while ignoring failed startups leads to survivor bias. Key Difference: \begin{center} \begin{tabular}{|c|c|c|} \hline Feature & Recall Bias & Survivor Bias
\hline Cause & Memory errors & Ignoring failed cases
\hline Occurs In & Surveys/interviews & Data analysis/selection
\hline Effect & Inaccurate reporting & Overly positive conclusions
\hline \end{tabular} \end{center} Conclusion: Recall bias arises from inaccurate memory during data collection, while survivor bias results from analyzing only successful outcomes and ignoring failures, both of which can distort statistical conclusions.