Among the numerous statistical analysis methods in SPSS, regression analysis mainly predicts whether there is a relationship between the independent and dependent variables, and whether the regression analysis data model has statistical significance. In regression analysis, sig is a very important parameter. To better understand the results of regression analysis, it is necessary to understand sig. Below, we will explain in detail what sig is in SPSS regression analysis and what to do if sig is zero in SPSS regression analysis.
1、 Why is the sig of SPSS regression analysis zero?
In SPSS regression analysis, the sig parameter represents whether there is a significant difference in the variables of the regression data model, that is, whether there is statistical significance. Simply put, whether the regression model data is necessary for further research and whether it can achieve the research objectives.
In SPSS statistical data analysis, there is a criterion for determining the sig parameter, with 0.05 as the standard. If the sig value is less than 0.05, it is significant; otherwise, if the sig value is greater than 0.05, it is not significant. Of course, this value is only a reference standard, and the specific situation needs to be judged based on actual research.
In SPSS regression analysis, a sig of zero indicates that the data variables in the regression analysis have significant differences. In practical regression analysis, the results of regression analysis will output many result tables, so the regression analysis results cannot only look at the parameter sig, but should be combined with the parameter values in the output results to make practical judgments.
Figure 1: Significance parameter
3、 How to solve the problem of zero sig in SPSS regression analysis?
In SPSS regression analysis, sig is not really zero, it's just that the values behind it are not displayed. Because in SPSS, for the convenience of displaying numerical values, only the first few digits are displayed by default in the output result table. Therefore, sometimes it may be seen that the sig value is zero, but in fact, the sig value at this time is infinitely close to zero and not really zero.
When writing a paper, if the regression analysis results show that sig is zero, it cannot be directly written as sig=0. It can be written as sig<0.01. Of course, if you want to know the specific amount of sig, you can check it in the pivot table. The specific steps are as follows.
1. Double click the table corresponding to the sig parameter to open the pivot table of this table.
Figure 2: ANOVA Table
2. In the pivot table window, find the corresponding value of the sig (significance) parameter in the table, double-click on the value, and you can see the specific value of sig.
Figure 3: Perspective Table
In SPSS regression analysis, sig is zero, indicating significant differences between regression analysis variables. However, sig is only a parameter indicator and cannot truly determine the quality of regression data. For example, the R-squared can be used to judge the fit of the regression model. The closer the value of the R-squared is to 1, the better the fit of the model.
Figure 4: R-square
In regression analysis, if sig is infinitely close to zero and the R-squared value is only 0.41, according to conventional judgment, the regression variable is significant and the model fit is not high. However, in actual analysis, the R-squared value of 0.41 is already very high for the field being studied. Therefore, if sig in regression analysis shows zero, it is also necessary to combine other parameter indicators for specific analysis.
