1. Correlation coefficient refers to a constant coefficient with a certain relationship or formula, and the correlation coefficient is an indicator of the degree of correlation between variables. The sample correlation coefficient is expressed by R, the overall correlation coefficient is expressed by ρ, and the range of correlation coefficient is [- 1, 1]. The larger the value of |r|, the smaller the error q and the higher the linear correlation between variables. The closer the value of |r| is to 0, the greater the q, and the lower the degree of linear correlation between variables. Critical value refers to the condition that a physical quantity must meet when an object changes from one physical state to another, which is equivalent to stagnation point in mathematics. Therefore, it is an important method to solve the maximum value and minimum value of physical quantities by using critical state, which is actually a dividing line.

2. The sample correlation coefficient is expressed by R, the overall correlation coefficient is expressed by ρ, and the range of correlation coefficient is [- 1, 1]. The larger the value of | r |, the smaller the error q and the higher the linear correlation between variables. The closer the value of |r| is to 0, the larger the q is.

1. Correlation is an uncertain relationship, and correlation coefficient is a measure to study the degree of linear correlation between variables. Because of the different research objects, the correlation coefficient can be defined in the following way. Simple correlation coefficient: also known as correlation coefficient or linear correlation coefficient, generally expressed by the letter R, used to measure the linear relationship between two variables. Definition: Cov(X, y) is the covariance of x and y, Var[X] is the variance of x, and Var[Y] is the variance complex correlation coefficient of y: also called complex correlation coefficient. Complex correlation refers to the correlation between dependent variable and multiple independent variables. For example, there is a complex correlation between the seasonal demand of a commodity and its price level and employee income level. Canonical correlation coefficient: Firstly, the original variables are analyzed by principal component analysis to get a new comprehensive index with linear relationship, and then the correlation between the original variables is studied through the linear correlation coefficient between the comprehensive indexes.

2. The value range of correlation coefficient is as follows: symbol: if it is a plus sign, it means positive correlation; If it is negative, it means negative correlation. Generally speaking, positive correlation means that the variable will change in the same direction as the reference number, and negative correlation means that the variable and the reference number change in the opposite direction. A value of 0 is an extreme value, indicating irrelevance. The value is 1, which means perfect positive correlation, and the change range in the same direction is the same. If it is-1, it means that there is a complete negative correlation, and it changes in the same direction. Value range: [- 1, 1].