|
Ecological Validity (perception)
This entry will describe the proper narrow and technical meaning of "ecological validity" as proposed by Egon Brunswik as part of the Brunswik Lens Model, the relation of "ecological validity" in "representative design" of research, and will outline the common misuses of the "ecological validity." For a more detailed explanation, see Hammond (1998). Proper Definition of Ecological Validity Egon Brunswik defined the term "ecological validity" in the 1940s to describe a cue's informativeness. The ecological validity of a sensory cue in perception is the regression weight the cue X (something an organism might be able to measure from the proximal stimulus) in predicting a property of the world Y (some aspect of the distal stimulus). The "ecological validity" of X1 is its multiple regression weight when Y is regressed on X1, X2, and X3. For example, the color of a banana is a cue that indicates whether the banana is ripe. This particular cue has high ecological validity becaus ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Egon Brunswik
Egon Brunswik Edler von Korompa (18 March 1903, Budapest7 July 1955, Berkeley, California) was a psychologist who made contributions to functionalism and the history of psychology. Life Early life and education Brunswik was born in Budapest, Hungary, then part of the Austro-Hungarian Empire. He graduated from the Theresianische Akademie in 1921, after studying mathematics, science, classics, and history. He enrolled as a student of psychology at the University of Vienna, where he became an assistant in Karl Bühler's Psychological Institute (student colleagues included Paul F. Lazarsfeld and Konrad Lorenz) and received a PhD in 1927. While a graduate student in psychology, he also passed the state examination for Gymnasium teachers in mathematics and physics. Early career Brunswik established the first psychological laboratory in Turkey while he was visiting lecturer in Ankara during 1931–1932. He became Privatdozent at the University of Vienna in 1934. In 1933, however, Edwar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sensory Cue
{{Disambiguation ...
Sensory may refer to: Biology * Sensory ecology, how organisms obtain information about their environment * Sensory neuron, nerve cell responsible for transmitting information about external stimuli * Sensory perception, the process of acquiring and interpreting sensory information * Sensory receptor, a structure that recognizes external stimuli * Sensory system, part of the nervous system of organisms Business and brands * Sensory, Inc., an American speech technology company Other uses * Sensory analysis, a consumer product-testing method * Sensory garden, a self-contained garden area that allows visitors to enjoy a wide variety of sensory experiences See also * Sensor * Sense (other) A sense in biology and psychology, is a physiological mechanism that supports perception. Sense also may refer to: Music * Sense (band), a synthpop trio featuring Paul K. Joyce * Sense (In the Nursery album), ''Sense'' (In the Nursery album), 199 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Perception
Perception () is the organization, identification, and interpretation of sensory information in order to represent and understand the presented information or environment. All perception involves signals that go through the nervous system, which in turn result from physical or chemical stimulation of the sensory system.Goldstein (2009) pp. 5–7 Vision involves light striking the retina of the eye; smell is mediated by odor molecules; and hearing involves pressure waves. Perception is not only the passive receipt of these signals, but it is also shaped by the recipient's learning, memory, expectation, and attention. Gregory, Richard. "Perception" in Gregory, Zangwill (1987) pp. 598–601. Sensory input is a process that transforms this low-level information to higher-level information (e.g., extracts shapes for object recognition). The process that follows connects a person's concepts and expectations (or knowledge), restorative and selective mechanisms (such as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Proximal Stimulus
Perception () is the organization, identification, and interpretation of sensory information in order to represent and understand the presented information or environment. All perception involves signals that go through the nervous system, which in turn result from physical or chemical stimulation of the sensory system.Goldstein (2009) pp. 5–7 Vision involves light striking the retina of the eye; smell is mediated by odor molecules; and hearing involves pressure waves. Perception is not only the passive receipt of these signals, but it is also shaped by the recipient's learning, memory, expectation, and attention. Gregory, Richard. "Perception" in Gregory, Zangwill (1987) pp. 598–601. Sensory input is a process that transforms this low-level information to higher-level information (e.g., extracts shapes for object recognition). The process that follows connects a person's concepts and expectations (or knowledge), restorative and selective mechanisms (such as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distal Stimulus
Perception () is the organization, identification, and interpretation of sensory information in order to represent and understand the presented information or environment. All perception involves signals that go through the nervous system, which in turn result from physical or chemical stimulation of the sensory system.Goldstein (2009) pp. 5–7 Vision involves light striking the retina of the eye; smell is mediated by odor molecules; and hearing involves pressure waves. Perception is not only the passive receipt of these signals, but it is also shaped by the recipient's learning, memory, expectation, and attention. Gregory, Richard. "Perception" in Gregory, Zangwill (1987) pp. 598–601. Sensory input is a process that transforms this low-level information to higher-level information (e.g., extracts shapes for object recognition). The process that follows connects a person's concepts and expectations (or knowledge), restorative and selective mechanisms (such as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Color
Color (American English) or colour (British English) is the visual perceptual property deriving from the spectrum of light interacting with the photoreceptor cells of the eyes. Color categories and physical specifications of color are associated with objects or materials based on their physical properties such as light absorption, reflection, or emission spectra. By defining a color space, colors can be identified numerically by their coordinates. Because perception of color stems from the varying spectral sensitivity of different types of cone cells in the retina to different parts of the spectrum, colors may be defined and quantified by the degree to which they stimulate these cells. These physical or physiological quantifications of color, however, do not fully explain the psychophysical perception of color appearance. Color science includes the perception of color by the eye and brain, the origin of color in materials, color theory in art, and the physics of electr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Banana
A banana is an elongated, edible fruit – botanically a berry – produced by several kinds of large herbaceous flowering plants in the genus ''Musa''. In some countries, bananas used for cooking may be called "plantains", distinguishing them from dessert bananas. The fruit is variable in size, color, and firmness, but is usually elongated and curved, with soft flesh rich in starch covered with a rind, which may be green, yellow, red, purple, or brown when ripe. The fruits grow upward in clusters near the top of the plant. Almost all modern edible seedless ( parthenocarp) bananas come from two wild species – ''Musa acuminata'' and ''Musa balbisiana''. The scientific names of most cultivated bananas are ''Musa acuminata'', ''Musa balbisiana'', and ''Musa'' × ''paradisiaca'' for the hybrid ''Musa acuminata'' × ''M. balbisiana'', depending on their genomic constitution. The old scientific name for this hybrid, ''Musa sapientum'', is no longer used. ''Musa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sticker
A sticker is a type of label: a piece of printed paper, plastic, vinyl, or other material with temporary or permanent pressure sensitive adhesive on one side. It can be used for decoration or for functional purposes, depending on the situation. Stickers can come in many different shapes and sizes and also vary widely in color and design. They are often adhered to items such as lunchboxes, paper, lockers, notebooks, walls, cars, windows, used as name tags, and so on. The term "sticker price" refers to the historic practice of adhering a large sticker to the window of a new car listing its base price, options, shipping charges, etc. (from which a discount was often negotiated). History R. Stanton Avery is credited with creating the first self-adhesive sticker in 1935. Use Stickers are very widely used when an object requires identification with a word or idea. Brand stickers may be attached to products to label these products as coming from a certain company. They ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Likelihood
The likelihood function (often simply called the likelihood) represents the probability of random variable realizations conditional on particular values of the statistical parameters. Thus, when evaluated on a given sample, the likelihood function indicates which parameter values are more ''likely'' than others, in the sense that they would have made the observed data more probable. Consequently, the likelihood is often written as \mathcal(\theta\mid X) instead of P(X \mid \theta), to emphasize that it is to be understood as a function of the parameters \theta instead of the random variable X. In maximum likelihood estimation, the arg max of the likelihood function serves as a point estimate for \theta, while local curvature (approximated by the likelihood's Hessian matrix) indicates the estimate's precision. Meanwhile in Bayesian statistics, parameter estimates are derived from the converse of the likelihood, the so-called posterior probability, which is calculated via Bayes' r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayesian Inference
Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability". Introduction to Bayes' rule Formal explanation Bayesian inference derives the posterior probability as a consequence of two antecedents: a prior probability and a "likelihood function" derived from a statistical model for the observed data. Bayesian inference computes the posterior probability according to Bayes' theorem: ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Inference
Statistical inference is the process of using data analysis to infer properties of an underlying probability distribution, distribution of probability.Upton, G., Cook, I. (2008) ''Oxford Dictionary of Statistics'', OUP. . Inferential statistical analysis infers properties of a Statistical population, population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is Sampling (statistics), sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population. In machine learning, the term ''inference'' is sometimes used instead to mean "make a prediction, by evaluating an already trained model"; in this context inferring properties of the model is referred to as ''training'' or ''learning'' (rather than ''inference''), and using a model for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cue Validity
Cue validity is the conditional probability that an object falls in a particular category given a particular feature or ''cue''. The term was popularized by , and especially by Eleanor Rosch in her investigations of the acquisition of so-called Prototype_theory#Basic_level_categories , ''basic categories'' (;). Definition of cue validity Formally, the cue validity of a feature f_i\ with respect to category c_j\ has been defined in the following ways: * As the conditional probability p(c_j, f_i)\ ; see , , . * As the deviation of the conditional probability from the category base rate, p(c_j, f_i)-p(c_j)\ ; see , . * As a function of the linear correlation; see , , , . * Other definitions; see , . For the definitions based on probability, a high cue validity for a given feature means that the feature or attribute is more diagnostic of the class membership than a feature with low cue validity. Thus, a high-cue validity feature is one which conveys more information about the categ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
