The variance is a figure that represents how far the data in your sample is clustered around the mean.  This figure will give you an idea of how far your data is spread out. Samples with low variance have data that is clustered closely about the mean. Samples with high variance have data that is clustered far from the mean. Variance is often used to compare the distribution of two data sets. This will give you a figure of how much each data point differs from the mean.  For example, in our sample of test scores (10, 8, 10, 8, 8, and 4) the mean or mathematical average was 8. 10 - 8 = 2; 8 - 8 = 0, 10 - 8 = 2, 8 - 8 = 0, 8 - 8 = 0, and 4 - 8 = -4. Do this procedure again to check each answer. It is very important you have each of these figures correct as you will need them for the next step. You will need each of these figures to find out the variance in your sample.  Remember, in our sample we subtracted the mean (8) from each of the numbers in the sample (10, 8, 10, 8, 8, and 4) and came up with the following: 2, 0, 2, 0, 0 and -4. To do the next calculation in figuring out variance you would perform the following: 22, 02, 22, 02, 02, and (-4)2 = 4, 0, 4, 0, 0, and 16. Check your answers before proceeding to the next step. This figure is called the sum of squares.  In our example of test scores, the squares were as follows: 4, 0, 4, 0, 0, and 16. Remember, in the example of test scores we started by subtracting the mean from each of the scores and squaring these figures: (10-8)^2 + (8-8)^2 + (10-8)^2 + (8-8)^2 + (8-8)^2 + (4-8)^2 4 + 0 + 4 + 0 + 0 + 16 = 24. The sum of squares is 24. Remember, n is how many numbers are in your sample. Doing this step will provide the variance. The reason to use n-1 is to have sample variance and population variance unbiased.    In our sample of test scores (10, 8, 10, 8, 8, and 4) there are 6 numbers. Therefore, n = 6. n-1 = 5. Remember the sum of squares for this sample was 24. 24 / 5 = 4.8 The variance in this sample is thus 4.8.

How would you rephrase that briefly using Vietnamese?
Tính phương sai. Lấy giá trị trung bình tính được ở bước trên trừ đi từng giá trị trong bộ số liệu. Bình phương tất cả các giá trị có được ở các phép trừ trên. Cộng tổng các giá trị sau khi đã bình phương ở trên, giá trị này còn được gọi là tổng bình phương. Chia tổng bình phương cho (n-1) với n là kích cỡ của bộ số liệu.