|
Interaction Variable
In statistics, an interaction may arise when considering the relationship among three or more variables, and describes a situation in which the effect of one causal variable on an outcome depends on the state of a second causal variable (that is, when effects of the two causes are not additive). Although commonly thought of in terms of causal relationships, the concept of an interaction can also describe non-causal associations (then also called ''moderation'' or ''effect modification''). Interactions are often considered in the context of regression analyses or factorial experiments. The presence of interactions can have important implications for the interpretation of statistical models. If two variables of interest interact, the relationship between each of the interacting variables and a third "dependent variable" depends on the value of the other interacting variable. In practice, this makes it more difficult to predict the consequences of changing the value of a variable, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
GSS Sealevel Interaction
GSS may refer to: Education * Garibaldi Secondary School, in Maple Ridge, British Columbia, Canada * Government Secondary School (other) * Greenridge Secondary School, in Singapore * Grimsby Secondary School, in Ontario, Canada * GSS Institute of Technology, in Bangalore, India * Gay Student Services, now GLBT Aggies, at Texas A&M University Government and politics * Global Standards Symposium * Civic Alliance of Serbia (Serbian: '), a political party in Serbia * Government Statistical Service, of the Government of the United Kingdom * Israeli General Security Service, also known as ''Shin Bet'' * Ghana Statistical Service, of the Government of Ghana Science * General Social Survey * Genome survey sequence * Gerstmann–Sträussler–Scheinker syndrome * Glutathione synthetase * Granulomatous slack skin * Gudjonsson suggestibility scale Sport * Grønlands Seminarius Sportklub, a Greenlandic sport club * Gurpreet Singh Sandhu, an Indian footballer * Panion ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Oscar Kempthorne
Oscar Kempthorne (January 31, 1919 – November 15, 2000) was a British statistician and geneticist known for his research on randomization-analysis and the design of experiments, which had wide influence on research in agriculture, genetics, and other areas of science. Born in St Tudy, Cornwall and educated in England, Kempthorne moved to the United States, where he was for many decades a professor of statistics at Iowa State University. Randomization analysis Kempthorne developed a randomization-based approach to the statistical analysis of randomized experiments, which was expounded in pioneering textbooks and articles. Kempthorne's insistence on randomization followed the early writings of Ronald Fisher, especially on randomized experiments. Kempthorne is the founder of the "Iowa school" of experimental design and analysis of variance. Kempthorne and many of his former doctoral students have often emphasized the use of the randomization distribution under the null hypothes ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Robust Regression
In robust statistics, robust regression seeks to overcome some limitations of traditional regression analysis. A regression analysis models the relationship between one or more independent variables and a dependent variable. Standard types of regression, such as ordinary least squares, have favourable properties if their underlying assumptions are true, but can give misleading results otherwise (i.e. are not robust to assumption violations). Robust regression methods are designed to limit the effect that violations of assumptions by the underlying data-generating process have on regression estimates. For example, least squares estimates for regression models are highly sensitive to outliers: an outlier with twice the error magnitude of a typical observation contributes four (two squared) times as much to the squared error loss, and therefore has more leverage over the regression estimates. The Huber loss function is a robust alternative to standard square error loss that r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ordinary Least Squares
In statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression In statistics, linear regression is a statistical model, model that estimates the relationship between a Scalar (mathematics), scalar response (dependent variable) and one or more explanatory variables (regressor or independent variable). A mode ... model (with fixed level-one effects of a linear function of a set of explanatory variables) by the principle of least squares: minimizing the sum of the squares of the differences between the observed dependent variable (values of the variable being observed) in the input dataset and the output of the (linear) function of the independent variable. Some sources consider OLS to be linear regression. Geometrically, this is seen as the sum of the squared distances, parallel to the axis of the dependent variable, between each data point in the set and the corresponding point on the regression ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Tea Party Interaction
Tea is an Aromaticity, aromatic drink, beverage prepared by pouring hot or boiling water over Curing (vegetable preservation), cured or fresh leaves of ''Camellia sinensis'', an evergreen shrub native to East Asia which probably originated in the borderlands of Southwest China, south-western China and Geography of Myanmar, northern Myanmar. Tea is also made, but rarely, from the leaves of ''Camellia taliensis''. After plain Drinking water, water, tea is the most widely consumed drink in the world. There are many types of tea; some have a cooling, slightly bitter, and astringent flavour, while others have profiles that include sweet, nutty, floral, or grassy Note (perfumery), notes. Tea has a Stimulant, stimulating effect in humans, primarily due to its caffeine content. An early credible record of tea drinking dates to the third century AD, in a medical text written by Chinese physician Hua Tuo. It was popularised as a recreational drink during the Chinese Tang dynasty, and te ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multicollinearity
In statistics, multicollinearity or collinearity is a situation where the predictors in a regression model are linearly dependent. Perfect multicollinearity refers to a situation where the predictive variables have an ''exact'' linear relationship. When there is perfect collinearity, the design matrix X has less than full rank, and therefore the moment matrix X^X cannot be inverted. In this situation, the parameter estimates of the regression are not well-defined, as the system of equations has infinitely many solutions. Imperfect multicollinearity refers to a situation where the predictive variables have a ''nearly'' exact linear relationship. Contrary to popular belief, neither the Gauss–Markov theorem nor the more common maximum likelihood justification for ordinary least squares relies on any kind of correlation structure between dependent predictors (although perfect collinearity can cause problems with some software). There is no justification for the pra ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dummy Variable (statistics)
In regression analysis, a dummy variable (also known as indicator variable or just dummy) is one that takes a binary value (0 or 1) to indicate the absence or presence of some categorical effect that may be expected to shift the outcome. For example, if we were studying the relationship between biological sex and income, we could use a dummy variable to represent the sex of each individual in the study. The variable could take on a value of 1 for males and 0 for females (or vice versa). In machine learning this is known as one-hot encoding. Dummy variables are commonly used in regression analysis to represent categorical variables that have more than two levels, such as education level or occupation. In this case, multiple dummy variables would be created to represent each level of the variable, and only one dummy variable would take on a value of 1 for each observation. Dummy variables are useful because they allow us to include categorical variables in our analysis, which ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stata
Stata (, , alternatively , occasionally stylized as STATA) is a general-purpose Statistics, statistical software package developed by StataCorp for data manipulation, visualization, statistics, and automated reporting. It is used by researchers in many fields, including biomedicine, economics, epidemiology, and sociology. Stata was initially developed by Computing Resource Center in California and the first version was released in 1985. In 1993, the company moved to College Station, Texas and was renamed Stata Corporation, now known as StataCorp. A major release in 2003 included a new graphics system and dialog boxes for all commands. Since then, a new version has been released once every two years. The current version is Stata 19, released in April 2025. Technical overview and terminology User interface From its creation, Stata has always employed an integrated command-line interface. Starting with version 8.0, Stata has included a graphical user interface which uses Menu ( ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
George Box
George Edward Pelham Box (18 October 1919 – 28 March 2013) was a British statistician, who worked in the areas of quality control, time-series analysis, design of experiments, and Bayesian inference. He has been called "one of the great statistical minds of the 20th century". He is famous for the quote "All models are wrong but some are useful". Education and early life He was born in Gravesend, Kent, England. Upon entering university he began to study chemistry, but was called up for service before finishing. During World War II, he performed experiments for the British Army exposing small animals to poison gas. To analyze the results of his experiments, he taught himself statistics from available texts. After the war, he enrolled at University College London and obtained a bachelor's degree in mathematics and statistics. He received a PhD from the University of London in 1953, under the supervision of Egon Pearson and Herman Otto Hartley, HO Hartley. Career and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
System
A system is a group of interacting or interrelated elements that act according to a set of rules to form a unified whole. A system, surrounded and influenced by its open system (systems theory), environment, is described by its boundaries, structure and purpose and is expressed in its functioning. Systems are the subjects of study of systems theory and other systems sciences. Systems have several common properties and characteristics, including structure, function(s), behavior and interconnectivity. Etymology The term ''system'' comes from the Latin word ''systēma'', in turn from Greek language, Greek ''systēma'': "whole concept made of several parts or members, system", literary "composition"."σύστημα" , Henry George Liddell, Robert Scott, ''A Greek–English Lexicon'', on Pers ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Genichi Taguchi
was an engineer and statistician. From the 1950s on, Taguchi developed a methodology for applying statistics to improve the quality of manufactured goods. Taguchi methods have been controversial among some conventional Western statisticians, but others have accepted many of the concepts introduced by him as valid extensions to the body of knowledge. Biography Taguchi was born and raised in the textile town of Tokamachi, in Niigata prefecture. He initially studied textile engineering at Kiryu Technical College with the intention of entering the family kimono business. However, with the escalation of World War II in 1942, he was drafted into the Astronomical Department of the Navigation Institute of the Imperial Japanese Navy. After the war, in 1948 he joined the Ministry of Public Health and Welfare, where he came under the influence of eminent statistician Matosaburo Masuyama, who kindled his interest in the design of experiments. He also worked at the Institute of Statist ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Additive Model
In statistics, an additive model (AM) is a nonparametric regression method. It was suggested by Jerome H. Friedman and Werner Stuetzle (1981) and is an essential part of the ACE algorithm. The ''AM'' uses a one-dimensional smoother to build a restricted class of nonparametric regression models. Because of this, it is less affected by the curse of dimensionality than a ''p''-dimensional smoother. Furthermore, the ''AM'' is more flexible than a standard linear model, while being more interpretable than a general regression surface at the cost of approximation errors. Problems with ''AM'', like many other machine-learning methods, include model selection, overfitting, and multicollinearity. Description Given a data set \_^n of ''n'' statistical units, where \_^n represent predictors and y_i is the outcome, the ''additive model'' takes the form : \mathrm x_, \ldots, x_= \beta_0+\sum_^p f_j(x_) or : Y= \beta_0+\sum_^p f_j(X_)+\varepsilon Where \mathrm \epsilon = 0, \mathrm(\e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
