What Bias is
Bias is an error in a statistic or an estimate of a parameter, caused by systematic departures from the assumed underlying theoretical model. It can be caused by sampling methods, data collection methods, or data analysis techniques. Bias can also be caused by non-random selection of the sample, non-representative samples, or incorrect data analysis.
Steps for Bias:
- Identify the source of bias. This can be done by examining the sampling method, data collection method, or data analysis technique.
- Determine the amount of bias. This can be done by calculating the difference between the expected value of the parameter and the actual value.
- Adjust the data or model. This can be done by correcting the samples or data collection methods or by adjusting the data analysis technique.
- Monitor the results. This can be done by tracking the difference between the expected value of the parameter and the actual value over time.
- Change the data collection and analysis methods if necessary. This can be done by changing the sampling method, data collection method, or data analysis technique to reduce or eliminate the bias.
Examples
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Sample Selection Bias: A researcher conducting a study on the effects of poverty on educational outcomes may select a sample of participants from a wealthier area of a city, leading to inaccurate results.
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Measurement Bias: A survey designed to measure customer satisfaction may be deliberately framed in a way that leads to an inflated perception of customer satisfaction.
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Selection Bias: A medical study may select participants who are healthier than the general population, leading to an underestimation of the true effects of a treatment.
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Confirmation Bias: A researcher may cherry-pick data points that support their existing hypothesis, while ignoring data points that contradict it.