linear regression

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Related to linear regression: Multiple linear regression
ThesaurusAntonymsRelated WordsSynonymsLegend:
Noun1.linear regression - the relation between variables when the regression equation is linear: e.g., y = ax + b
statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
regression toward the mean, simple regression, statistical regression, regression - the relation between selected values of x and observed values of y (from which the most probable value of y can be predicted for any value of x)
regression coefficient - when the regression line is linear (y = ax + b) the regression coefficient is the constant (a) that represents the rate of change of one variable (y) as a function of changes in the other (x); it is the slope of the regression line
References in periodicals archive ?
For predicting live weight of goats, multiple linear regression analysis is often applied to data regarding live weight-morphological linear traits (Adeyinka and Mohammed, 2006; Alade et al.
The absorbance was observed at 221 nm in the derivative mode and linear regression equation was calculated.
With the results obtained from linear regression analysis, the researcher had confirmed and summarised that all the hypotheses proposed in this research are approved and accepted.
In the factor analysis, three new latent variables whose eigenvalues were greater than one were considered as explanatory variable for multiple linear regression analysis.
Review of research, revealed the widespread use of simple linear regression (Williams and Gregoire 1993; Williams and Schreuder 1996; Marshall et al.
The multiple linear regression models are the most important method of predicting the yield by its components.
If the original relationship is exponential, the graph of the transformed values will be linear and a straight line can be fitted using the methods of linear regression described previously.
This paper provides an Edgeworth expansion for the distribution of the maximum likelihood estimators (MLE) of the parameter of a time series generated by a linear regression model with Gaussian, stationary, long-memory errors.
The discussion below assumes a basic understanding of linear regression (for more details, see box, "Further Reading.
Among the several options, the linear regression and the kriging interpolation methods are the most interesting (Fiala, 2009).
The intermediate/advanced level will cover importing and converting other data formats; creating relational databases; advanced check-coding and using Epi Info functions; advanced analysis including linear regression, logistic regression, Kaplan Meier, Cox proportional hazards, complex sample frequencies, tables, and means; special topics on Epi Map and Epi Report; and issues related to students' own projects.
Key words: Business result, strategy, multiple linear regression, variables.