1) That's called the regression line and the intercept is called alpha--there's alpha.

2) That is , the regression line would tend to overestimate the magnitudes of Y.

3) The correlation coefficient y-intercept slope of the regression line and residual sum of squares should be submitted.

4) Data from the regression line itself may be helpful to provide mathematical estimates of the degree of linearity.

5) The regression line is derived from a sample and not from the entire population.

6) Based on the slope value of log-probit regression line, the resistance of Txinnabarinus to abamectin could continue develop to a higher level,[http:///regression line.html] but the developmental rate would be slow.

7) Plot the areas of the sum of silybin A and silybin B peaks versus the concentration of USP Silybin RS in the Silybin standard solutions, and obtain a regression line for calibration.

8) Computes the average of the independent variable of the regression line.

9) Non-linearity error is determined by difference between a calibration po- int and regression line.

10) Also, it can change the intercept and slope of the regression line.

11) The standard error of estimate, on the other hand, measures the variability, or scatter, of the observed values around the regression line.

12) Least-square principle method was used to process experimental data and the regression line obtained. The failure mechanism of the He-Ne laser tube under different current has been analyzed.

13) Besides, the history of least one-power method and least squares method, multiple solutions and the various effects of outliers on the regression line are discussed.

14) How do we think about how well our sample regression line fits our sample data?

15) What Gauss did was said, let's fit a line through the point-- the scatter of points--and that's called the regression line.

16) As a result, the conditions under which the influencing variable in a regression line equation is collapsible are derived .

17) If there appears to be a linear relationship test results should be established by appropriate statistical methods (e. g. by calculation of a regression line by the method of least squares).

18) There are critical points to distinguish different percolation mechanism on Klinkenberg regression line.

19) If the observations used in the analysis extend back in time for several years, the resulting regression line may be too steep.

20) Based on the fact that total error is needed by the system, this thesis emphasizes particularly on analyzing the static regression line error model and its engineering feasibility.

21) A new correlation coefficient that indicates goodness of-fit for regression line will be introduced yet in this paper. The illustrative examples are presented.