(1) First, arrange the average values from big to small (from top to bottom), and mark the letter A after the largest average value.

(2) compare the average with each average in turn (downward process), mark the same letter A whenever the difference is not significant, and then mark the letter B until you meet an average with significant difference, and stop the downward comparison;

(3) Take the average marked with the letter B as the standard, and compare it with the above average which is larger than it in turn (upward process). If the difference is not significant, mark B again until it is significant (start to "turn around" downwards);

(4) Take the maximum average marked with the letter B as the standard (downward process) and compare it with the average of unmarked letters in turn. If the difference is not significant, continue to mark the letter b until you meet an average score c with significant difference;

(5) This cycle continues until the smallest average value is marked, and the comparison ends.

Marking method of "moves": The data is the diameter of disease spots after different pathogenic fungi strains infect plant leaves. SPSS data and analysis results have been uploaded to the forum, and you can download the exercises. To make multiple comparisons with SPSS, we need to get three tables, namely descriptive, variance homogeneity test and multiple comparisons. From the results of Levene variance homogeneity test (P = 0.496 >；; 0.05) indicates that LSD (minimum significant difference) method is suitable for multiple comparisons. Next, copy and paste the "descriptive" table into Excel, sort it slightly, and then sort it in reverse order of the average value.

Knowledge extension definition of difference significance: difference significance is a significant difference and a statistical term. It is an evaluation of data differences in statistics. Usually, when the experimental results reach 0.05 or 0.0 1, it can be said that there are significant or extremely significant differences between the data. Principle: When there are significant differences between the data, it means that the data involved in the comparison are not from the same population, but from two different populations with differences. This difference may be due to the fact that the data involved in the comparison come from different experimental subjects. For example, in some general ability tests, there will be significant differences between the test group with college education and the test group with primary education. It may also come from the fact that the experimental treatment has caused fundamental personality changes to the experimental subjects, so the data before and after the test will be obviously different.