Dependent and independent variablesDependent and independent variables are variables in mathematical modeling, statistical modeling and experimental sciences. Dependent variables are studied under the supposition or demand that they depend, by some law or rule (e.g., by a mathematical function), on the values of other variables. Independent variables, in turn, are not seen as depending on any other variable in the scope of the experiment in question. In this sense, some common independent variables are time, space, density, mass, fluid flow rate, and previous values of some observed value of interest (e.
Maximum spacing estimationIn statistics, maximum spacing estimation (MSE or MSP), or maximum product of spacing estimation (MPS), is a method for estimating the parameters of a univariate statistical model. The method requires maximization of the geometric mean of spacings in the data, which are the differences between the values of the cumulative distribution function at neighbouring data points.
Percussion instrumentA percussion instrument is a musical instrument that is sounded by being struck or scraped by a beater including attached or enclosed beaters or rattles struck, scraped or rubbed by hand or struck against another similar instrument. Excluding zoomusicological instruments and the human voice, the percussion family is believed to include the oldest musical instruments. In spite of being a very common term to designate instruments, and to relate them to their players, the percussionists, percussion is not a systematic classificatory category of instruments, as described by the scientific field of organology.
Linear regressionIn statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.
Ordinary least squaresIn statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression 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.
Estimation of covariance matricesIn statistics, sometimes the covariance matrix of a multivariate random variable is not known but has to be estimated. Estimation of covariance matrices then deals with the question of how to approximate the actual covariance matrix on the basis of a sample from the multivariate distribution. Simple cases, where observations are complete, can be dealt with by using the sample covariance matrix.
Keyboard instrumentA keyboard instrument is a musical instrument played using a keyboard, a row of levers that are pressed by the fingers. The most common of these are the piano, organ, and various electronic keyboards, including synthesizers and digital pianos. Other keyboard instruments include celestas, which are struck idiophones operated by a keyboard, and carillons, which are usually housed in bell towers or belfries of churches or municipal buildings. Today, the term keyboard often refers to keyboard-style synthesizers.
Electronic musical instrumentAn electronic musical instrument or electrophone is a musical instrument that produces sound using electronic circuitry. Such an instrument sounds by outputting an electrical, electronic or digital audio signal that ultimately is plugged into a power amplifier which drives a loudspeaker, creating the sound heard by the performer and listener. An electronic instrument might include a user interface for controlling its sound, often by adjusting the pitch, frequency, or duration of each note.
Wind instrumentA wind instrument is a musical instrument that contains some type of resonator (usually a tube) in which a column of air is set into vibration by the player blowing into (or over) a mouthpiece set at or near the end of the resonator. The pitch of the vibration is determined by the length of the tube and by manual modifications of the effective length of the vibrating column of air. In the case of some wind instruments, sound is produced by blowing through a reed; others require buzzing into a metal mouthpiece, while yet others require the player to blow into a hole at an edge, which splits the air column and creates the sound.
Experimental musical instrumentAn experimental musical instrument (or custom-made instrument) is a musical instrument that modifies or extends an existing instrument or class of instruments, or defines or creates a new class of instrument. Some are created through simple modifications, such as cracked drum cymbals or metal objects inserted between piano strings in a prepared piano. Some experimental instruments are created from household items like a homemade mute for brass instruments such as bathtub plugs.
Homoscedasticity and heteroscedasticityIn statistics, a sequence (or a vector) of random variables is homoscedastic (ˌhoʊmoʊskəˈdæstɪk) if all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity, also known as heterogeneity of variance. The spellings homoskedasticity and heteroskedasticity are also frequently used.
Endogeneity (econometrics)In econometrics, endogeneity broadly refers to situations in which an explanatory variable is correlated with the error term. The distinction between endogenous and exogenous variables originated in simultaneous equations models, where one separates variables whose values are determined by the model from variables which are predetermined; ignoring simultaneity in the estimation leads to biased estimates as it violates the exogeneity assumption of the Gauss–Markov theorem.
