Unbiased Analysis and Interpretation
Explore how to recognize and mitigate common biases like selection, outlier, and confirmation bias in data analysis. Understand steps to create unbiased visualizations and narratives. Learn techniques to maintain accuracy and build trust in your data storytelling process.
There are several ways bias can trickle into data analysis and interpretation. Human cognitive biases can exacerbate and add issues in data processes, quickly leading data storytellers to tell false stories and their audiences to form incorrect conclusions. Bias is particularly challenging to enforce as a best practice because multiple forms of are difficult to detect. Let’s look at a few fundamental forms of bias that can influence data analysis and interpretation.
Data selection and analysis
Let’s briefly look at what types of biases can form during the data selection and analysis stages.
Selection bias
Selection bias occurs when the data samples we've gathered do not represent the real-world population. Data visualization can help identify forms of selection bias.
For example, data ...