The function of Pearson correlation analysis in spss is simply to consider the relationship between variables. Although multiple variables can be placed at the same time in the analysis process, the result is that there is a simple correlation between the two variables, that is, other control variables are not considered when calculating the correlation between the two variables.
The result of regression is the combination of all the independent variables and dependent variables that enter the regression equation, which means that the correlation you see in regression is after controlling other variables that enter the regression equation.
take for example
If you check the relationship between variables A, B and C, if you use conventional correlation, the results will show simple correlation between A and B, simple correlation between B and C and simple correlation between A and C. Correlation only involves two variables, and has nothing to do with the third variable.
However, in the case of regression, the correlation between A and B is after subtracting the influence of C variable, while the correlation between B and C is after subtracting the influence of A, and the correlation between A and C is after subtracting the influence of B ... Different calculation methods lead to different results.
Baidu Encyclopedia-Correlation Analysis