Data Biases
Definition
Data biases refer to systematic errors or prejudices present in a dataset that can lead to inaccurate or unfair conclusions when analyzing the data.
Analogy
Imagine you are conducting a survey about favorite ice cream flavors but accidentally only ask people at an ice cream shop. The resulting data would be biased towards popular flavors at that specific shop, rather than representing everyone's preferences accurately.
Related terms
Sampling Bias: Sampling bias occurs when certain groups within a population are more likely to be included in a sample than others, leading to skewed results.
Confirmation Bias: Confirmation bias refers to the tendency of individuals to interpret information in a way that confirms their preexisting beliefs or hypotheses.
Algorithmic Bias: Algorithmic bias occurs when machine learning algorithms produce discriminatory outcomes due to biased training datasets or flawed programming.
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