# regression coefficient

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Related to regression coefficient: correlation coefficient

## Regression coefficient

Term yielded by regression analysis that indicates the sensitivity of the dependent variable to a particular independent variable. See: Parameter.

## Regression Coefficient

A mathematical measure of the effect that an independent variable has on a dependent variable. It may be used on any number of financial measures. For example, one may calculate the effect that earnings have on the share price.

## regression coefficient

A mathematical measure of the relationship between a dependent variable and an independent variable. For example, a financial theorist might attempt to determine the effect of increased dividends on a stock's price by calculating the regression coefficient between the price of the stock and its dividends per share. In this instance, the stock price is the dependent variable and the dividend payment is the independent variable.
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The regression coefficient was calculated by plotting the graph between various parameters, and it was observed that it has shown good correlation (regression coefficient, [R.sup.2] > 0.95, is given in table 5).
The regression coefficient is 0.120885, which means that if NPF increases by 10%, the sharia banking financing supply increases by 12.08%.
Combining these random-regression coefficients with the fixed regression coefficients of the lactation curve related to an individual cow's environment (e.g., herd or calving season) will provide an estimate of the total milk yield during that cow's lactation.
For the characteristics of the compression of the regression coefficient, the experiment set should be sparse, as well as one dependent variable which is easy to distinguish.
Consequently, we have chosen the model with one component for OSC + PLS and the model with 7 components for PLS because they give the best results, and also because they have approximatively the same RMSE allowing us to compare the stability of regression coefficients independently.
In the regression analysis, when multi collinearity phenomenon between variables, often will seriously affect the expansion of parameter estimation, model error, and damage the robustness of model, thus eliminating multi collinearity has become an important part in the estimation of regression coefficients.
A genotype that has a regression coefficient (bi) = 1 and the regression coefficient deviation ([CD.sup.2]) = 0 means the genotype is stable.
To verify whether the proposed model actually describe the experimental data, the multiple regression coefficient were computed.
HA, in terms of the percentage of goals scored by home teams, was derived from the Tincom' regression coefficient (beta) for match location (0=Away, 1=Home) using the following formula.
The regression coefficient of parental STEM occupation was 0.45 and the odds ratio was.
a = air adp = apparatus dew point in = indoor return air max = maximum out = outdoor ambient air rat = at rating condition wb = wet bulb 0-5 = regression coefficient REFERENCES

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