If the regression coefficient is greater than zero, the correlation coefficient is greater than zero; If the regression coefficient is less than zero, the correlation coefficient is less than zero. (They have the same symbol)

Regression coefficient: derived from the derivative of regression equation, so regression coefficient >; 0, the curve of the regression equation is monotonically increasing; When the regression coefficient is less than 0, the curve of regression equation decreases monotonously; Regression coefficient =0, and the regression equation finds the maximum value (maximum value, minimum value).

Regression coefficient is a parameter indicating the influence of independent variable X on dependent variable Y in regression equation. The greater the regression coefficient, the greater the influence of X on Y. A positive regression coefficient means that Y increases with the increase of X. ..

A negative regression coefficient means that Y decreases with the increase of X. For example, in the regression equation Y=bX+a, the slope B is called the regression coefficient, which means that every unit of X changes, on average, Y will change by B units.

Extended data

Properties of correlation coefficient r:

1、? r？ ≤ 1;

2. When r > 0, it shows that the two variables are positively correlated; When r < 0, the two variables are negatively correlated;

3、? r？ The closer to 1, the stronger the linear correlation between the two variables;

4、? r？ The closer to 0, the weaker the linear correlation between the two variables;

5. Usually? r？ > 0.75, there is a strong linear relationship between the two variables.

6. If there is a strong linear relationship between two variables, this straight line is called regression straight line, and the equation obtained is regression straight line equation.

Baidu encyclopedia-regression coefficient

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