The mean square is the value that we will use to estimate different variances.

均是我们用来估计不同差的值。

So, the mean square is the sum of squares divided by the degrees of freedom.

因此， 均是除以自由度。

The expected mean square represents the variance that the mean square column is estimating.

预期均表均列估计的差。

To find the variance of each source of variation, we have to use the expected mean square (EMS).

为了个变异源的差， 我们必须使用预期均 (EMS)。

So, we will just present the expected mean squares.

因此， 我们将仅呈现预期均。

The parts expected mean square is shown below.

预期均部分如下所。

This is what is estimated by the mean square for parts.

这是通过零件均估计的值。

The mean square is the estimate of the variance for that source of variability based on the amount of data we have (the degrees of freedom).

均是基于我们拥有的数据量（自由度）对该变异源的差的估计。

The mean square is the estimate of the variance for that source of variability (not necessarily by itself) based on the amount of data we have (the degrees of freedom).

均是基于我们拥有的数据量（自由度）对该变异源（不一定是其本身）的差的估计。

We completed the ANOVA table, presented the expected mean squares and how to use those to estimate the variances of the components, and showed how to determine the %GRR as a percent of the total variance.

我们完成了差分析表， 提出了预期均以及如何使用这些均来估计各分量的差，并展了如何确定 %GRR 占总差的百分比。

The fifth column is the F value. This is determined by dividing the mean square for the treatments by the mean square error. It is this value that determines if there are any significant differences between the treatment means.

第五列是F值。这是通过将处理的均除以均误差来确定的。正是这个值决定了处理均值之间是否存在显着差异。