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Experimental Bias
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 * Reactivity (psychology), Reactivity bias, a bias resulting from participants behaving differently when they know they are being observed. In survey research this is sometimes called response bias. ** Hawthorne effect, often relates to improving performance in response to an intervention ** John Henry effect, sometimes relates to a behavioural change due to rivalry between groups, which may have negative outcomes ** Observer-expectancy effect, is when researcher expectatio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neutral Point Of View
Neutral or neutrality may refer to: Mathematics and natural science Biology * Neutral organisms, in ecology, those that obey the unified neutral theory of biodiversity Chemistry and physics * Neutralization (chemistry), a chemical reaction in which an acid and a base react quantitatively with each other * Neutral solution, a chemical solution which is neither acidic nor basic * Neutral particle, a particle without electrical charge Mathematics * Neutral element or identity element, in mathematics, a special element with respect to a binary operation, such that if the operation is applied to any element in a set, that element is unchanged * Neutral vector, a multivariate random variable that exhibits a particular type of statistical independence (Dirichlet distribution) Philosophy * Neutrality (philosophy), the absence of declared or intentional bias * Neutrality (psychoanalysis) * Neutral level, the physical or material traces of esthesic and poietic processes identified in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bias (statistics)
In the field of statistics, bias is a systematic tendency in which the methods used to gather data and estimate a sample statistic present an inaccurate, skewed or distorted ('' biased'') depiction of reality. Statistical bias exists in numerous stages of the data collection and analysis process, including: the source of the data, the methods used to collect the data, the estimator chosen, and the methods used to analyze the data. Data analysts can take various measures at each stage of the process to reduce the impact of statistical bias in their work. Understanding the source of statistical bias can help to assess whether the observed results are close to actuality. Issues of statistical bias has been argued to be closely linked to issues of statistical validity. Statistical bias can have significant real world implications as data is used to inform decision making across a wide variety of processes in society. Data is used to inform lawmaking, industry regulation, corp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Grid Bias
In electronics, biasing is the setting of DC (direct current) operating conditions (current and voltage) of an electronic component that processes time-varying signals. Many electronic devices, such as diodes, transistors and vacuum tubes, whose function is processing time-varying ( AC) signals, also require a steady (DC) current or voltage at their terminals to operate correctly. This current or voltage is called ''bias''. The AC signal applied to them is superposed on this DC bias current or voltage. The operating point of a device, also known as bias point, quiescent point, or Q-point, is the DC voltage or current at a specified terminal of an active device (a transistor or vacuum tube) with no input signal applied. A bias circuit is a portion of the device's circuit that supplies this steady current or voltage. Overview In electronics, 'biasing' usually refers to a fixed DC voltage or current applied to a terminal of an electronic component such as a diode, transistor ... [...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 several mathematical measures of bias, which can disagree slightly, but all measures broadly agree that rules based on Droop's quota or Jefferson's method are strongly biased in favor of large parties, while rules based on Webster's method, Hill's method, or Hare's quota have low levels of bias, with the differences being sufficiently small that different definitions of bias produce different results. 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' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neural Network
A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or signal pathways. While individual neurons are simple, many of them together in a network can perform complex tasks. There are two main types of neural networks. *In neuroscience, a '' biological neural network'' is a physical structure found in brains and complex nervous systems – a population of nerve cells connected by synapses. *In machine learning, an '' artificial neural network'' is a mathematical model used to approximate nonlinear functions. Artificial neural networks are used to solve artificial intelligence problems. In biology In the context of biology, a neural network is a population of biological neurons chemically connected to each other by synapses. A given neuron can be connected to hundreds of thousands of synapses. Each neuron sends and receives electrochemical signals called action potentials to its conne ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Inductive Bias
The inductive bias (also known as learning bias) of a learning algorithm is the set of assumptions that the learner uses to predict outputs of given inputs that it has not encountered. Inductive bias is anything which makes the algorithm learn one pattern instead of another pattern (e.g., step-functions in decision trees instead of continuous functions in linear regression models). Learning involves searching a space of solutions for a solution that provides a good explanation of the data. However, in many cases, there may be multiple equally appropriate solutions. An inductive bias allows a learning algorithm to prioritize one solution (or interpretation) over another, independently of the observed data. In machine learning, the aim is to construct algorithms that are able to learn to predict a certain target output. To achieve this, the learning algorithm is presented some training examples that demonstrate the intended relation of input and output values. Then the learner is s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Exponent Bias
In IEEE 754 floating-point numbers, the exponent is biased in the engineering sense of the word – the value stored is offset from the actual value by the exponent bias, also called a biased exponent. Biasing is done because exponents have to be signed values in order to be able to represent both tiny and huge values, but two's complement, the usual representation for signed values, would make comparison harder. To solve this problem the exponent is stored as an unsigned value which is suitable for comparison, and when being interpreted it is converted into an exponent within a signed range by subtracting the bias. By arranging the fields such that the sign bit takes the most significant bit position, the biased exponent takes the middle position, then the significand will be the least significant bits and the resulting value will be ordered properly. This is the case whether or not it is interpreted as a floating-point or integer value. The purpose of this is to enable high sp ... [...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-processing). 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 information-processing rules (i.e., mental shortcuts), called ''heuristics'', that the brain uses to produce decisions or judgments. Biases have a variety of forms and appear as cognitive ("cold") bias, such as mental noise, or motivational ("hot") bias, such as when bel ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Confirmation Bias
Confirmation bias (also confirmatory bias, myside bias, or congeniality bias) is the tendency to search for, interpret, favor and recall information in a way that confirms or supports one's prior beliefs or Value (ethics and social sciences), 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. 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 ''irrational primacy effect'' (a greater relia ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cognitive Bias
A cognitive bias is a systematic pattern of deviation from norm (philosophy), norm or rationality in judgment. Individuals create their own "subjective reality" from their perception of the input. An individual's construction of reality, not the Objectivity (philosophy), objective input, may dictate their behavior in the world. Thus, cognitive biases may sometimes lead to perceptual distortion, inaccurate judgment, illogical interpretation, and irrationality. While cognitive biases may initially appear to be negative, some are adaptive. They may lead to more effective actions in a given context. Furthermore, allowing cognitive biases enables faster decisions which can be desirable when timeliness is more valuable than accuracy, as illustrated in Heuristic (psychology), heuristics. Other cognitive biases are a "by-product" of human processing limitations, resulting from a lack of appropriate mental mechanisms (bounded rationality), the impact of an individual's constitution and bi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reporting Bias
In epidemiology, reporting bias is defined as "selective revealing or suppression of information" by subjects (for example about past medical history, smoking, sexual experiences). In artificial intelligence research, the term reporting bias is used to refer to people's tendency to under-report all the information available. In empirical research, authors may be under-reporting unexpected or undesirable experimental results, attributing the results to sampling or measurement error, while being more trusting of expected or desirable results, though these may be subject to the same sources of error. In this context, reporting bias can eventually lead to a status quo where multiple investigators discover and discard the same results, and later experimenters justify their own reporting bias by observing that previous experimenters reported different results. Thus, each incident of reporting bias can make future incidents more likely. Reporting biases in research Research can only co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
