What are some common data collection errors I should be aware of?
An example of an AI chatbot conversation about common data collection errors.
What are some common data collection errors I should be aware of?
Common data collection errors include sampling bias, measurement errors, and data entry mistakes.
Can you explain sampling bias?
Sampling bias occurs when the sample collected is not representative of the population, leading to skewed results.
What can I do to avoid measurement errors?
To avoid measurement errors, ensure proper calibration of instruments and use standardized procedures.
How can I check for data entry mistakes?
You can check for data entry mistakes by implementing double data entry, validation rules, and regular audits.
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