SPSS statistical analysis is a method system for data processing and analysis using SPSS software. The system has three core functional modules: data management, statistical analysis, and visual output. Adopting a menu driven and graphical interface interaction method, it supports data import in Excel and other formats, and has more than 20 statistical models such as mean calculation, variance analysis, and factor analysis built-in. As an excellent data statistical analysis software, SPSS has many data analysis methods, but regardless of which data analysis method is used, the sig parameter can be seen in the analysis results.
So is sig the p-value in SPSS?
Some colleagues may have questions about the sig and p-value in the SPSS analysis results. Is sig a p-value? In fact, sig and p-value are two different terms under the same concept. The difference is that sig is a term used in SPSS result analysis, while p-value is a term used in statistical analysis. In practical application analysis, the two can be considered as the same parameter.
In SPSS, when sig is less than 0.05, it indicates that the null hypothesis is not valid but the result is significant. When sig shows zero, it indicates that the sig value is less than 0.01, indicating that the result is very significant. When sig is greater than 0.05, it indicates that the null hypothesis is valid but the result is not significant.
The p-value is used in statistics to determine the probability of the null hypothesis being true, usually with a threshold of 0.05. When the p-value is greater than 0.05, the confidence interval of the null hypothesis is less than 95%. If the p-value is less than 0.05, the confidence interval of the null hypothesis is greater than 95%, which can also be used to determine the significance of the variable.
Figure 1: Sig significance
2、 How to view sig values in SPSS
The sig value of SPSS is mainly viewed based on the analysis method and results. Taking the independent sample t-test method as an example, we will explain in detail how to view the sig value.
1. Assuming that the variables in the dataset follow a normal distribution, click on the "Analyze" - "Compare Mean and Proportion" - "Independent Sample t-test" option in the SPSS menu bar.
Figure 2: Select independent sample t-test option
2. In the Independent Sample T-Test window, move the analysis variables on the left to the Test Variables and the grouped variables to the Grouping Variables box. Click the Define Group button to group the variables in the pop-up Define Group window. Click the Continue button to return to the Independent Sample T-Test window, and then click the OK button.
Figure 3: Independent sample t-test window
3. In the independent sample test table below, it can be seen that the sig (significance) of blood glucose and uric acid are 0.915 and 0.299, respectively, both greater than the reference value of 0.05. In the following analysis, only the first row of data is needed. However, it should be noted that if the sig value is greater than 0.05, it indicates that the p-value is also greater than 0.05. In statistics, a p-value greater than 0.05 indicates that the average difference between the two groups of data is not statistically significant.
Figure 4: Independent Sample Testing Table
