R square is the decisive factor, that is, the percentage change of the dependent variable that can be explained by the fitting model. For example, R-square = 0.8 10, which means that the fitting equation can explain the dependent variable variation of 8 1% and the unexplained variation of 19%.

F is variance test, the global test of the whole model, to see if it is meaningful to fit the equation.

T value is to test each independent variable one by one (logistic regression) to see if its beta value, that is, the regression coefficient, is meaningful.

The significance of f and t is 0.05,

Regression analysis is the most commonly used statistical method in scientific research. SPSS regression analysis introduces some basic statistical methods, such as correlation, regression (linear, multivariate and nonlinear), logic (binomial and polynomial), ordered regression and survival analysis (life table method, Kaplan-Meier method and Cox regression).

SPSS is the earliest statistical analysis software in the world. 1968 Norman. Nie, C Hadley (Tex) Hull and Daley. Bent, three graduate students from Stanford University, successfully carried out research and development. At the same time, SPSS company was established.

Extended information:

Principle:

This representation depends on the percentage change of the variable y that can be explained by the control variable X.

The determining coefficient is not equal to the square of the correlation coefficient. The difference between this coefficient and the correlation coefficient is that if | is removed, r | is equal to 0 and 1.

Because R2