The analysis of variance (ANOVA) table above shows the results of a statistical test that compares the variation between groups to the variation within groups. In this case, the test is being used to determine if there is a significant difference between the means of two groups.

The table is divided into three main sections: Source, DF (degrees of freedom), and Sum of Squares. The Source column indicates the source of variation being analyzed, which in this case is the Model and Error. The DF column shows the degrees of freedom associated with each source of variation. The Sum of Squares column shows the amount of variation associated with each source.

The Mean Square column is calculated by dividing the Sum of Squares by the degrees of freedom. This value represents the average amount of variation associated with each source.

The F Ratio column shows the result of the F-test, which is calculated by dividing the Mean Square for the Model by the Mean Square for the Error. This value is used to determine if there is a significant difference between the means of the two groups. In this case, the F Ratio is 2.7533.

The Prob > F value indicates the probability of obtaining an F Ratio as extreme as the one observed, assuming that there is no significant difference between the means of the two groups. In this case, the Prob > F value is 0.0981, which means that there is a 9.81% chance of obtaining an F Ratio as extreme as the one observed, assuming that there is no significant difference between the means of the two groups.

Overall, the ANOVA table provides a statistical summary of the variation between and within groups, and allows us to determine if there is a significant difference between the means of the two groups being compared.