Assumed mean takes a ballpark guess at the mean, then uses math to calculate a number close to the mean. It is assumed because it does not go into an actual mean calculation. It is important to remember that the only time you should use assumed mean is if you have very small amounts of data in your data set. So if your data set consists of more than 20 entries, you should not use assumed mean.
Sort your data set from smallest to largest. For example, assume your data set is 43, 45, 46, 48 and 49.
Assume a mean. This should be a number that you feel is a close representation of your data set. In the example, assume your mean is 46.
Subtract your assumed mean from each data entry. In the example, 43 minus 46 equals -3, 45 minus 46 equals -1, 46 minus 46 equals 0, 48 minus 46 equals 2 and 49 minus 46 equals 3.
Add together each difference from the mean. In the example, -3 plus -1 plus 0 plus 2 plus 3 equals 1.
Divide the sum of the differences from assumed mean by number of data points. In the example, 1 divided by 5 equals 0.2.
Add the result of the division to your assumed mean. In the example, 46 plus 0.2 equals an assumed mean of 46.2.