linear regression

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Related to linear regression: Multiple linear regression

linear regression

a statistical procedure in which a straight line is established through a data set that best represents a relationship between two subsets or two methods.

linear regression

A statistical method defined by the formula y = mx = b which is used to "best-fit" straight lines to scattered data points of paired values Xi, Yi, where the values of Y—the ordinate or vertical line—are “observations” or values of a variable (e.g., systolic blood pressure) and the values of X—the abscissa or horizontal line—increased in a relatively nonrandom fashion (e.g., age). Linear regression is a parametric procedure for determining the relationship between one or more (multiple) continuous or categorical predictor (or independent) variables and a continuous outcome (or dependent) variable.

In the equation y = mx = b:
m = slope
b = y - intercept

linear regression

Statistics A statistical method defined by the formula y = a + bx, which is used to 'fit' straight lines to scattered data points of paired values Xi, Yi, where the values of Y–the ordinate or vertical line are observations of a variable–eg, systolic BP and the values of X–the abscissa or horizontal line ↑ in a relatively nonrandom fashion–eg, age

linear regression

A statistical method of predicting the value of one variable, given the other, in a situation in which a CORRELATION is known to be significant. The equation is y = a + bx in which x and y are, respectively, the independent and dependent variables and a and b are constants. This is an equation for a straight line.

linear

in a line.

linear assessment
a method of expressing an assessment result as a score out of a possible perfect score of 10, or some other number. Used in body condition scoring, showring judging of conformation.
linear dodecyl benzene sulfonic acid teat dip
linear energy transfer
expresses the quality of electronic radiation. It is concerned with the spatial distributions of energy transfers which occur in the tracks of particles as they penetrate matter.
linear program
a management program used to determine the best mix of ingredients or services to be used in a particular situation to maintain the highest level of productivity or profitability or other similar parameter.
linear regression
statistical method used to study the relationship between independent and dependent variables when the dependent variable consists of continuous data.
linear score
for somatic cell counts in milk (SCCs) convert SCC logarithmically from cells per milliliter to a linear score from 0-9. The linear score has a straight line, inverse relationship with milk yield. An increase of one in the linear score is associated with a 400-pound decrease in lactation milk yield or a 1.5 pound drop in daily yield.

regression

2. subsidence of clinical signs or of a disease process.
3. in biology, the tendency in successive generations toward the mean.
4. the relationship between pairs of random variables; the mean of one variable and its location is influenced by another variable.

regression analysis
see regression analysis.
regression coefficient
is the factor which determines the slope of a regression line; the greater the coefficient the steeper the line.
curvilinear regression
when the relationship between two variables is not linear.
linear regression
the relationship between two variables is a straight line.
References in periodicals archive ?
In the present study, summary results of multiple linear regression, use of factor score in multiple regression analysis, and principal component regression for male and female goat are given in Table 8.
The multiple linear regression equation for fitting standardized body weight and the following factor score equation can be formulated as below:
In order to select the best simple linear regression model between the two variables In order to select the best simple linear regression model between the two variable Basal area (independent) and variable percentage of tree canopy (dependent), a summary of fit statistics are presented in Table 5.
Many times, a simple plot of the data suggests a nonlinear relationship, and the use of variants of linear regression may be beneficial.
Best results were obtained when linear regression and kriging were applied to the CHIMERE model data for rural stations and only kriging for urban ones and using population as surrogate indicator for merging urban and rural maps.
The results of the simple linear regression line for each variable with average points per game indicated that both were important and statistically significant (defensive rebounds: t(18) equals 6.
Health policy practitioners find linear regression to be valuable because of its overall interpretability and ease of use (Sheingold 1990), so ideally an alternative to standard linear regression should be readily interpretable as well.
Hypothesis model regression test of multiple linear regressions was obtained by value of variable regression coefficient of GRDP at CMV to per capita income obtained value equal to 1.
Linear regression is limited to predicting numeric output.
To address the research question and achieve the objective of the study, correlation and statistical linear regression analysis was done to predict the values of response variables (dependent variables: physico-chemical characteristics of SPM) through explanatory variables (independent variable: physico-chemical characteristics of inert matter/material/waste) .
2012), using multiple linear regression model, estimated rice grain yield incorporating to the model the number of panicles [m.

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