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Biased
Bias is an inclination toward something, or a predisposition, partiality, prejudice, preference, or predilection. Bias may also refer to: Scientific method and statistics * The bias introduced into an experiment through a confounder * Algorithmic bias, machine learning algorithms that exhibit politically unacceptable behavior * Cultural bias, interpreting and judging phenomena in terms particular to one's own culture * Funding bias, bias relative to the commercial interests of a study's financial sponsor * Infrastructure bias, the influence of existing social or scientific infrastructure on scientific observations * Publication bias, bias toward publication of certain experimental results * Bias (statistics), the systematic distortion of a statistic ** Biased sample, a sample falsely taken to be typical of a population ** Estimator bias, a bias from an estimator whose expectation differs from the true value of the parameter * Personal equation, a concept in 19th- and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Estimator Bias
In statistics, the bias of an estimator (or bias function) is the difference between this estimator's expected value and the true value of the parameter being estimated. An estimator or decision rule with zero bias is called ''unbiased''. In statistics, "bias" is an property of an estimator. Bias is a distinct concept from consistency: consistent estimators converge in probability to the true value of the parameter, but may be biased or unbiased; see bias versus consistency for more. All else being equal, an unbiased estimator is preferable to a biased estimator, although in practice, biased estimators (with generally small bias) are frequently used. When a biased estimator is used, bounds of the bias are calculated. A biased estimator may be used for various reasons: because an unbiased estimator does not exist without further assumptions about a population; because an estimator is difficult to compute (as in unbiased estimation of standard deviation); because a biased estimato ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Confirmation Bias
Confirmation bias is the tendency to search for, interpret, favor, and recall information in a way that confirms or supports one's prior beliefs or values. People display this bias when they select information that supports their views, ignoring contrary information, or when they interpret ambiguous evidence as supporting their existing attitudes. The effect is strongest for desired outcomes, for emotionally charged issues, and for deeply entrenched beliefs. Confirmation bias cannot be eliminated, but it can be managed, for example, by education and training in critical thinking skills. Biased search for information, biased interpretation of this information, and biased memory recall, have been invoked to explain four specific effects: # ''attitude polarization'' (when a disagreement becomes more extreme even though the different parties are exposed to the same evidence) # ''belief perseverance'' (when beliefs persist after the evidence for them is shown to be false) # the ''irr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Algorithmic Bias
Algorithmic bias describes systematic and repeatable errors in a computer system that create "unfair" outcomes, such as "privileging" one category over another in ways different from the intended function of the algorithm. Bias can emerge from many factors, including but not limited to the design of the algorithm or the unintended or unanticipated use or decisions relating to the way data is coded, collected, selected or used to train the algorithm. For example, algorithmic bias has been observed in search engine results and social media platforms. This bias can have impacts ranging from inadvertent privacy violations to reinforcing social biases of race, gender, sexuality, and ethnicity. The study of algorithmic bias is most concerned with algorithms that reflect "systematic and unfair" discrimination. This bias has only recently been addressed in legal frameworks, such as the European Union's General Data Protection Regulation (2018) and the proposed Artificial Intelligence A ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bias (statistics)
Statistical bias is a systematic tendency which causes differences between results and facts. The bias exists in numbers of the process of data analysis, including the source of the data, the estimator chosen, and the ways the data was analyzed. Bias may have a serious impact on results, for example, to investigate people's buying habits. If the sample size is not large enough, the results may not be representative of the buying habits of all the people. That is, there may be discrepancies between the survey results and the actual results. Therefore, understanding the source of statistical bias can help to assess whether the observed results are close to the real results. Bias can be differentiated from other mistakes such as accuracy (instrument failure/inadequacy), lack of data, or mistakes in transcription (typos). Bias implies that the data selection may have been skewed by the collection criteria. Bias does not preclude the existence of any other mistakes. One may have a poo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Biased Sample
In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected. If this is not accounted for, results can be erroneously attributed to the phenomenon under study rather than to the method of sampling. Medical sources sometimes refer to sampling bias as ascertainment bias. Ascertainment bias has basically the same definition, but is still sometimes classified as a separate type of bias. Distinction from selection bias Sampling bias is usually classified as a subtype of selection bias, sometimes specifically termed sample selection bias, but some classify it as a separate type of bias. A distinction, albeit not universally accepted, of sampling bias is that it undermines the external validity of a test (the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bias
Bias is a disproportionate weight ''in favor of'' or ''against'' an idea or thing, usually in a way that is closed-minded, prejudicial, or unfair. Biases can be innate or learned. People may develop biases for or against an individual, a group, or a belief. In science and engineering, a bias is a systematic error. Statistical bias results from an unfair sampling of a population, or from an estimation process that does not give accurate results on average. Etymology The word appears to derive from Old Provençal into Old French ''biais'', "sideways, askance, against the grain". Whence comes French ''biais'', "a slant, a slope, an oblique". It seems to have entered English via the game of bowls, where it referred to balls made with a greater weight on one side. Which expanded to the figurative use, "a one-sided tendency of the mind", and, at first especially in law, "undue propensity or prejudice". Types of bias Cognitive biases A cognitive bias is a repeating or basic mi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
List Of Cognitive Biases
Cognitive biases are systematic patterns of deviation from norm and/or rationality in judgment. They are often studied in psychology, sociology and behavioral economics. Although the reality of most of these biases is confirmed by reproducible research, there are often controversies about how to classify these biases or how to explain them. Several theoretical causes are known for some cognitive biases, which provides a classification of biases by their common generative mechanism (such as noisy information-processingMartin Hilbert (2012) "Toward a synthesis of cognitive biases: How noisy information processing can bias human decision making"'. Psychological Bulletin, 138(2), 211–237; free access to the study here: https://www.martinhilbert.net/toward-a-synthesis-of-cognitive-biases/). Gerd Gigerenzer has criticized the framing of cognitive biases as errors in judgment, and favors interpreting them as arising from rational deviations from logical thought. Explanations include ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Seat Bias
Seat bias is a property describing methods of apportionment. These are methods used to allocate seats in a parliament among federal states or among political parties. A method is ''biased'' if it systematically favors small parties over large parties, or vice versa. There are various ways to compute the bias of apportionment methods. When the agents are federal states, it is particularly important to avoid bias between large states and small states. There are several ways to measure this bias formally. Notation There is a positive integer h (=house size), representing the total number of seats to allocate. There is a positive integer n representing the number of parties to which seats should be allocated. There is a vector of fractions (t_1,\ldots,t_n) with \sum_^n t_i = 1, representing ''entitlements'' - t_i represents the entitlement of party i, that is, the fraction of seats to which i is entitled (out of the total of h). This is usually the fraction of votes that this part ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
