Biased sample
Biased Sample is a statistical term that refers to a sample of a population that does not accurately represent the entire population. It is a sample that, due to its composition, tends to produce results that are skewed in a certain direction or favor certain outcomes.
Definition[edit | edit source]
A biased sample is a subset of a statistical population in which all members of the subset do not have an equal chance of being selected. This can result in a significant deviation in the sample from the general population, leading to skewed results that do not accurately represent the population.
Types of Biased Samples[edit | edit source]
There are several types of biased samples, including:
- Convenience sampling: This type of sampling involves selecting individuals who are easiest to reach or readily available. This method is often used due to its convenience, but it can lead to bias as it may not accurately represent the entire population.
- Voluntary response sampling: This type of sampling involves individuals choosing themselves by responding to a general appeal. This can lead to bias as individuals with strong opinions or motivations are more likely to participate.
- Undercoverage: This occurs when some members of the population are inadequately represented in the sample. This can lead to bias as it can skew the results in favor of the overrepresented group.
Effects of Biased Samples[edit | edit source]
The effects of a biased sample can significantly impact the results of a study or survey. It can lead to misleading statistics and inaccurate conclusions about the population. This can have serious implications in fields such as medicine, politics, and market research where accurate representation is crucial.
Avoiding Biased Samples[edit | edit source]
To avoid biased samples, researchers should aim to use random sampling techniques where each member of the population has an equal chance of being selected. Additionally, researchers should strive for a large sample size to increase the likelihood that the sample accurately represents the population.
See Also[edit | edit source]
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