In the field of data statistics, measuring SPSS test values can compare and analyze complex data groups, which is helpful for conducting subsequent research on data associations and differences.
1、 How to view SPSS test values
When comparing two sets of data, we can use methods such as SPSS t-test and chi square test to determine whether there are differences in specific numerical aspects. Next, taking t-test as an example, we will demonstrate how to interpret SPSS test values.
1. Case data refers to the output values of different teams in a certain aspect, as shown in the following figure, which are the output data of teams 1 and 2 respectively. We need to use t-test to analyze the differences in output values between team 1 and team 2.
Figure 1: Output values of two teams
2. Firstly, in the analysis column of the SPSS data editor, find 'Compare Average', click on the 'Single Sample t-test' option, and enter the set test value to determine the significance of the output value data of two teams.
Figure 2: Module for Setting Test Values in SPSS
3. Move the output value to the 'Test Variables' column. Based on the above case data, we can set the test value to 5.5 to see the difference between the specific output value and this set value. Then check the' Estimate Effect Size 'and click the' OK 'button.
Figure 3: Set the inspection value to 5.5
4. Afterwards, the results of the single sample test were obtained on the SPSS output page. The number of cases with output values was 10. Compared with the set test value, the significance of the output values of the two teams was p<0.001, indicating a significant difference from the value of 5.5.
Figure 4: Single sample test results of two teams
二、How to obtain SPSS test values
Single sample t-test is mainly used to test whether there is a significant difference between actual data and set data. SPSS t-test and independent sample test methods can be used to compare the mean values of two sets of data. Let's take the output values of Team 1 and Team 2 from the above case data as an example to demonstrate how SPSS test values are obtained.
1. Find the 'Compare Mean' function in the analysis module, select the 'Independent Sample t-test', enter the functional module for inter group difference analysis, and then observe and analyze whether there is a significant difference in output between Team 1 and Team 2.
Figure 5: Data difference between two teams in terms of mean
2. To move the output value to the 'test variable' and the team to the 'grouping variable', we need to group the existing case data team 1 and team 2.
Figure 6: Using teams as grouping variables
3. Then click the 'Define Group' button, fill in 1 in the Group 1 column and 2 in the Group 2 column under 'Use specified values', click the' Continue 'button, and check the' Estimate effect size 'module to complete the variable settings for Team 1 and Team 2.
Figure 7: Grouping with specified values
4. On the results display page of the independent sample test, we can see that assuming an isoscedasticity p=0.873, the test can be passed, and then the significance test value p<0.001 indicates that there is a significant difference in output values between Team 1 and Team 2.
Figure 8: Inspection results of two teams
