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Topics referred to by the same term
Variable analysis may refer to: Bivariate analysis Multivariate analysis Univariate analysis This disambiguation page lists articles associated with the
Variable_analysis
Branch of mathematics studying functions of a complex variable
Complex analysis, traditionally known as the theory of functions of a complex variable, is the branch of mathematical analysis that studies complex-valued
Complex_analysis
Compiler optimization
In compilers, live variable analysis (or simply liveness analysis) is a classic data-flow analysis to calculate the variables that are live at each point
Live-variable_analysis
Mathematics of real numbers and real functions
Real analysis is also known, especially in older books, as the theory of functions of a real variable, in contrast to the theory of complex variables. The
Real_analysis
Numeric stand-ins in regression analysis
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
Dummy_variable_(statistics)
Concept in mathematical modeling, statistical modeling and experimental sciences
A variable is considered dependent if it depends on (or is hypothesized to depend on) an independent variable. Dependent variables are the outcome of the
Dependent and independent variables
Dependent_and_independent_variables
Set of statistical processes for estimating the relationships among variables
regression analysis is a statistical method for estimating the relationship between a dependent variable (often called the outcome or response variable, or a
Regression_analysis
hierarchical loglinear analysis (restricted to a maximum of 8 variables) loglinear analysis (to identify relevant/important variables and possible confounders)
Data_analysis
Statistical model
or process by which one variable influences another variable through a mediator variable. In particular, mediation analysis can contribute to better
Mediation_(statistics)
In computer science, an induction variable is a variable that gets increased or decreased by a fixed amount on every iteration of a loop or is a linear
Induction_variable
Statistical method
Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved
Factor_analysis
Concept in statistical analysis
Bivariate analysis is one of the simplest forms of quantitative (statistical) analysis. It involves the analysis of two variables (often denoted as X
Bivariate_analysis
Method used in statistics, pattern recognition, and other fields
categorical independent variables and a continuous dependent variable, whereas discriminant analysis has continuous independent variables and a categorical
Linear_discriminant_analysis
Analysis methods in linguistics
Variable rules analysis is a set of statistical analysis methods in linguistics that are commonly used in sociolinguistics and historical linguistics to
Variable_rules_analysis
Statistical model relating manifest and latent variables
profile analysis. In factor analysis and latent trait analysis the latent variables are treated as continuous normally distributed variables, and in latent
Latent_variable_model
Area of mathematical analysis
Fourier analysis. The Fourier transform remains a fundamental tool in harmonic analysis. But much of modern real-variable harmonic analysis is concerned
Harmonic_analysis
Simultaneous observation and analysis of more than one outcome variable
encompassing the simultaneous observation and analysis of more than one outcome variable, i.e., multivariate random variables. Multivariate statistics concerns understanding
Multivariate_statistics
Method of analyzing variables in software
variable might propagate. The information gathered is often used by compilers when optimizing a program. A canonical example of a data-flow analysis is
Data-flow_analysis
Branch of mathematics
study variable quantities, and in the 19th century its foundations were reformulated with greater rigor. Basic objects of study in mathematical analysis include
Mathematical_analysis
Variable capable of taking on a limited number of possible values
considering data analysis, it is common to use the term "categorical data" to apply to data sets that, while containing some categorical variables, may also
Categorical_variable
Types of numerical variables in mathematics
generally in regression analysis, sometimes some of the variables being empirically related to each other are 0-1 variables, being permitted to take
Continuous or discrete variable
Continuous_or_discrete_variable
Topics referred to by the same term
Look up Variable, variable, or variables in Wiktionary, the free dictionary. Wikiversity has learning resources about Variable Variable may refer to:
Variable
Variable representing a random phenomenon
cases is not always straightforward. The purely mathematical analysis of random variables is independent of such interpretational difficulties, and can
Random_variable
Compiler that optimizes generated code
loops include: Induction variable analysis Roughly, if a variable in a loop is a simple linear function of the index variable, such as j := 4*i + 1, it
Optimizing_compiler
Statistical method in psychology
exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique
Exploratory_factor_analysis
Statistical modeling method
joint probability distribution of all of these variables, which is the domain of multivariate analysis. A generalization of linear regression is found
Linear_regression
General linear model that blends ANOVA and regression
dependent variable (DV) are equal across levels of one or more categorical independent variables (IV) and across one or more continuous variables. For example
Analysis_of_covariance
Statistical term
In statistics, path analysis is used to describe the directed dependencies among a set of variables. This includes models equivalent to any form of multiple
Path_analysis_(statistics)
Statistics concept
regression analysis, moderation (also known as effect modification) occurs when the relationship between two variables depends on a third variable. The third
Moderation_(statistics)
Concept in statistics
Dependent and independent variables Errors-in-variables models Evidence lower bound Factor analysis Intervening variable Latent variable model Item response
Latent and observable variables
Latent_and_observable_variables
Study of uncertainty in the output of a mathematical model or system
occurrence of stochastic events. In models involving many input variables, sensitivity analysis is an essential ingredient of model building and quality assurance
Sensitivity_analysis
Method of data analysis
component analysis for categorical data. Principal component analysis creates variables that are linear combinations of the original variables. The new
Principal_component_analysis
Factorial method
factor analysis (MFA) is a factorial method devoted to the study of tables in which a group of individuals is described by a set of variables (quantitative
Multiple_factor_analysis
Unit selling price minus its variable cost
per unit minus the variable cost per unit. "Contribution" represents the portion of sales revenue that is not consumed by variable costs and so contributes
Contribution_margin
Process of understanding a complex topic or substance
involving several variables, such as by factor analysis, regression analysis, or principal component analysis Principal component analysis – transformation
Analysis
Function theory with quaternion variable
variable just as functions of a real variable or a complex variable are called. As with complex and real analysis, it is possible to study the concepts
Quaternionic_analysis
Mathematical function
texts, the theory of functions of a real variable is often synonymous with what is usually now called real analysis. The most widely considered such functions
Function_of_a_real_variable
Type of statistical bias
missing variables to those that were included. More specifically, OVB is the bias that appears in the estimates of parameters in a regression analysis, when
Omitted-variable_bias
Analytic method in statistics
multiple correspondence analysis (MCA) for qualitative variables. When data include both types of variables but the active variables being homogeneous, PCA
Factor_analysis_of_mixed_data
Aspect of probability and statistics
the data analysis being done, involves a wider set of random variables but that attention is being limited to a reduced number of those variables. In many
Marginal_distribution
Type of mathematical functions
several complex variables (and analytic space), which the Mathematics Subject Classification has as a top-level heading. As in complex analysis of functions
Function of several complex variables
Function_of_several_complex_variables
Type of statistics
analysis is that bivariate analysis is not only a simple descriptive analysis, but also it describes the relationship between two different variables
Descriptive_statistics
Computing and logic method
optimization analysis is a more complex extension of goal-seeking analysis. Instead of setting a specific target value for a variable, the goal is to
Goal_seeking
Statistical model for a binary dependent variable
event as a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) estimates the parameters
Logistic_regression
Method in electric circuit analysis
analysis (with the corresponding network variables called loop currents) can be applied to any circuit, planar or not.[citation needed] Mesh analysis
Mesh_analysis
Form of causal modeling that fit networks of constructs to data
LISREL embedded latent variables (which psychologists knew as the latent factors from factor analysis) within path-analysis-style equations (which sociologists
Structural_equation_modeling
Electronics Engineers (IEEE) in 2015 for contributions to latent variable analysis. "2015 elevated fellow" (PDF). IEEE Fellows Directory. Archived from
Mark_Plumbley
Bias in causal inference
be a variable that (1) independently predicts the outcome (or dependent variable), (2) is associated with the exposure (or independent variable), and
Confounding
Branch of statistics
predictor variables, an alternative method is Cox proportional hazards regression analysis. Cox PH models work also with categorical predictor variables, which
Survival_analysis
Open-source SEM software package for R
Free and open-source software portal lavaan, short for "Latent variable analysis", is an open-source structural equation modeling (SEM) package for the
Lavaan
regression analysis, an antecedent variable would be one that influences both the independent variable and the dependent variable. Path analysis (statistics)
Antecedent_variable
Design of tasks
more independent variables, also referred to as "input variables" or "predictor variables." The change in one or more independent variables is generally hypothesized
Design_of_experiments
Cost accounting model
decisions. A critical part of CVP analysis is the point where total revenues equal total costs (both fixed and variable costs). At this break-even point
Cost–volume–profit_analysis
Approximation method in statistics
standard regression analysis that leads to fitting by least squares there is an implicit assumption that errors in the independent variable are zero or strictly
Least_squares
Uncertainty analysis investigates the uncertainty of variables that are used in decision-making problems in which observations and models represent the
Uncertainty_analysis
Branch of statistics
of data. In statistics, regression analysis is a statistical process for estimating the relationships among variables. It includes many ways for modeling
Mathematical_statistics
American sociologist (1900–1987)
Association and his Presidential Address was his paper "Sociological Analysis and the 'Variable'". Blumer was also elected as the president of the Society for
Herbert_Blumer
Subgroup analysis refers to repeating the analysis of a study within subgroups of subjects defined by a subgrouping variable. For example: smoking status
Subgroup_analysis
Technique in statistics
the explanatory variable (the variable correlated with the endogenous variable) but has no independent effect on the dependent variable and is not correlated
Instrumental_variables
Immune disorder
Common variable immunodeficiency (CVID) is an inborn immune disorder characterized by recurrent infections and low antibody levels, specifically in immunoglobulin
Common variable immunodeficiency
Common_variable_immunodeficiency
Concept in statistical mathematics
or broken-stick regression, is a method in regression analysis in which the independent variable is partitioned into intervals and a separate line segment
Segmented_regression
Statistical test
the two-way analysis of variance (ANOVA) is used to study how two categorical independent variables affect one continuous dependent variable. It extends
Two-way_analysis_of_variance
How many standard deviations apart from the mean an observed datum is
cluster analysis, the concept of distance between the units in the data is often of considerable interest and importance… When the variables in a multivariate
Standard_score
American academic
genome-wide gene expression data. Leek and Storey introduced "surrogate variable analysis", which is a high-dimensional regression model that includes both
John_D._Storey
Causal or moderating relationship between statistical variables
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
Interaction_(statistics)
Classification of variables in economic models
variable is one whose measure is determined outside the model and is imposed on the model. An exogenous change is a change in an exogenous variable.
Exogenous and endogenous variables
Exogenous_and_endogenous_variables
Numerical measure of a statistical relationship between variables
type of linear correlation, meaning a linear function between two variables. The variables may be two columns of a given data set of observations, often called
Correlation_coefficient
Property of an intermediate representation in a compiler
"block-local" variables are omitted. Computing the set of block-local variables is a simpler and faster procedure than full live-variable analysis, making semi-pruned
Static_single-assignment_form
Design of experiments to collect similar contexts together
work in developing analysis of variance (ANOVA) set the groundwork for grouping experimental units to control for extraneous variables. Blocking evolved
Blocking_(statistics)
Analysis of the dimensions of different physical quantities
variables. A dimensional equation can have the dimensions reduced or eliminated through nondimensionalization, which begins with dimensional analysis
Dimensional_analysis
Collection of statistical models
Polish by Jerzy Neyman in 1923. The analysis of variance can be used to describe otherwise complex relations among variables. A dog show provides an example
Analysis_of_variance
reachable uses analysis is a data-flow analysis to calculate all reachable uses of a program. It is very similar to the liveness analysis. A variable is live
Upwards_exposed_uses
Procedure for comparing multivariate sample means
form of univariate analysis of variance (ANOVA), although, unlike univariate ANOVA, it uses the covariance between outcome variables in testing the statistical
Multivariate analysis of variance
Multivariate_analysis_of_variance
Branch of mathematics
restrictive for functions of a complex variable than it is for functions of a real variable. Complex analysis studies holomorphic functions, the differentiable
Calculus
Symbol representing a mathematical object
that the variable represents or denotes the object, and that any valid candidate for the object is the value of the variable. The values a variable can take
Variable_(mathematics)
Statistical linear model
the analysis of multiple brain scans in scientific experiments where Y contains data from brain scanners, X contains experimental design variables and
General_linear_model
Economics analysis
area, state, or any other region of the country. The analysis examines changes in an economic variable, such as migration, a demographic statistic, firm
Shift-share_analysis
Study of collection and analysis of data
potential confusion it can cause. Statistical analysis of a data set often reveals that two variables (properties) of the population under consideration
Statistics
Data analysis technique
too small for linear regression analysis but large enough for cross-case analysis. In the case of categorical variables, QCA begins by listing and counting
Qualitative comparative analysis
Qualitative_comparative_analysis
Regression models accounting for possible errors in independent variables
errors-in-variables model or a measurement error model is a regression model that accounts for measurement errors in the independent variables. In contrast
Errors-in-variables_model
Equality of costs and revenues
terms—that is required to cover total costs, consisting of both fixed and variable costs to the company. Total profit at the break-even point is zero. It
Break-even_point
the analysis of such experiments, particularly where the experimental design is subject to randomization, treat these factors as random variables. More
Nuisance_variable
Transfer of information within a process
are given once it is decrypted. In low level information flow analysis, each variable is usually assigned a security level. The basic model comprises
Information flow (information theory)
Information_flow_(information_theory)
Statistical test
F distribution). This analysis of variance technique requires a numeric response variable "Y" and a single explanatory variable "X", hence "one-way".
One-way_analysis_of_variance
Computer code that is never executed
program. Dead code analysis can be performed using live-variable analysis, a form of static-code analysis and data-flow analysis. This is in contrast
Dead_code
which can be used for the analysis of categorical data, also known as data on the nominal scale and as categorical variables. Bowker's test of symmetry
List of analyses of categorical data
List_of_analyses_of_categorical_data
Collection of random variables
process is a mathematical object usually defined as a family of random variables in a probability space, where the index of the family often has the interpretation
Stochastic_process
Statistical relationship
correlation is a type of statistical relationship between two random variables or bivariate data. It usually refers to the extent to which a pair of
Correlation
Extension to cover cases with multiple dependent variables
dependent variables. An example is provided by the analysis of trend in sea-level by Woodworth (1987). Here the dependent variable (and variable of most
Multivariate analysis of covariance
Multivariate_analysis_of_covariance
Type of statistical model
these. The dependent variable must be examined at the lowest level of analysis. When there is a single level 1 independent variable, the level 1 model is
Multilevel_model
Procedures to optimize practices in cost efficient ways
obtained. To validate this analysis the table below shows the income statement of the company including additional orders: Variable costs as a percentage of
Cost_accounting
Technique used in statistics
Log-linear analysis is a technique used in statistics to examine the relationship between more than two categorical variables. The technique is used for
Log-linear_analysis
Form of statistical factor analysis
exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are employed to understand shared variance of measured variables that is believed
Confirmatory_factor_analysis
Variation in the time intervals between heartbeats
the beat-to-beat interval is a physiological phenomenon. Power spectral analysis of the beat-to-beat variations of heart rate or the heart period (R–R interval)
Heart_rate_variability
Indicator for how well data points fit a line or curve
proportion of the variation in the dependent variable that is predictable from the independent variable(s). It is a statistic used in the context of statistical
Coefficient_of_determination
Data analysis technique
the different groups of variables) within a global analysis and provides, beyond the classical results of factorial analysis (mainly graphics of individuals
Multiple correspondence analysis
Multiple_correspondence_analysis
Statistical technique
variance explained (model R2) of all the independent variables on the dependent variable. Commonality analysis produces 2k − 1 commonality coefficients, where
Commonality_analysis
binomial distribution bivariate analysis A type of quantitative statistical analysis in which exactly two variables are analyzed, for the purpose of
Glossary of probability and statistics
Glossary_of_probability_and_statistics
Theorem
mathematical analysis about the Cesàro convergence of a subsequence of random variables (or functions) and their subsequences to an integrable random variable (or
Komlós'_theorem
American biostatistician and data scientist
issues in translational genomics," Parker proposed frozen surrogate variable analysis (fSVA) to improve prediction accuracy in public genomic studies and
Hilary_Parker
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