Bias (statistics)

From WikiMD's Wellness Encyclopedia

Bias (statistics) is a systematic error introduced into sampling or testing by selecting or encouraging one outcome or answer over others[1]. It is a deviation of results or inferences from the truth, or processes leading to such deviation. Bias can lead to inaccurate conclusions about a population or process based on the data from a sample.

Types of Bias[edit | edit source]

There are several types of bias in statistics, including:

  • Selection bias: This occurs when the sample obtained is not representative of the population intended to be analyzed.
  • Confirmation bias: This is a tendency to search for, interpret, favor, and recall information in a way that confirms one's preexisting beliefs or hypotheses.
  • Publication bias: This occurs when the outcome of an experiment or research study influences the decision whether to publish or otherwise distribute it.
  • Survivorship bias: This is the logical error of concentrating on the people or things that made it past some selection process and overlooking those that did not.

Effects of Bias[edit | edit source]

Bias can significantly affect the validity of a study or survey. It can lead to over- or under-estimations of certain characteristics or results. In medical research, for example, bias can lead to incorrect conclusions about the efficacy of a treatment or the prevalence of a disease.

Controlling Bias[edit | edit source]

Bias can be controlled or minimized through various methods, including:

  • Randomization: This is the practice of assigning subjects to different treatment groups in an unpredictable manner.
  • Blinding: This is a practice to prevent bias in research where the people involved are prevented from knowing certain information that might lead to bias.
  • Replication: This involves repeating a study using the same methods but different subjects and experimenters.

See Also[edit | edit source]

References[edit | edit source]

  1. "Bias (statistics)". Britannica. Retrieved 2021-09-30.



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