errors in data analysis

What are the Types of Errors in Data Analysis?

Errors in data analysis can be broadly classified into two categories: random errors and systematic errors.
Random Errors
Random errors are unpredictable variations that occur during data collection and analysis. They are often caused by inherent variability in the population or measurement processes. These errors can lead to imprecise results but do not bias the findings in any specific direction.
Systematic Errors
Systematic errors, also known as biases, are consistent and repeatable errors that occur in the data collection or analysis process. These errors can skew results in a particular direction, leading to invalid conclusions. Examples include selection bias, information bias, and confounding.

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