regression equation


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Noun1.regression equation - the equation representing the relation between selected values of one variable (x) and observed values of the other (y); it permits the prediction of the most probable values of y
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 analysis - the use of regression to make quantitative predictions of one variable from the values of another
equation - a mathematical statement that two expressions are equal
References in periodicals archive ?
The regression equation to estimate stature derived from the right foot index of males is given in Table 2.
Hence, the objective of the present study was to determine the effect of the inclusion levels on the DE and ME values of cottonseed oil using the difference method and evaluate the ELF and TTTD for cottonseed oil by the regression equation.
To formulate the empirical model and regression equation, Design Expert 7 statistical software was used.
The joint evaluation of the intercept and slope coefficient in the regression Equation for observed versus predicted values for BW (Table 2) rejects the null hypothesis (p < 0.
2012) reported that when using regression models for estimates, the values of the independent variable to be estimated should not extrapolate the values used in the construction of the regression equation.
The first step in fitting a regression equation to the data set in Figure 1 is to plot the data in a scattergraph in Excel (see Figure 2).
j] by the method of least squares, the regression equation can be used for setting the estimate of variable Y with certain precision.
Using odds, the logistic regression equation can be written as under:
1] is the unit characteristic vector corresponding to the maximum eigenvalue of the matrix, and then the regression equation is obtained.
The effects of plant characters of brinjal were correlated with the population of jassids and calculated their impact by processing the data into simple and multiple linear regression equation.
The increase in irrigation water salinity negatively affected 'Crioula' guava SD and, according to the regression equation (Figure 1A), there was a decreasing linear effect, with reduction of 4.