The answer will depend on the context.
The mean absolute deviation is the sum of the differences between data values and the mean, divided by the count. In this case it is 15.7143
sum means addition so the sum of 5 and 2 will be 7
The sum of the differences between each score in a distribution and the mean of those scores is always zero because the mean is defined as the balance point of the distribution. When you subtract the mean from each score, the positive differences (scores above the mean) exactly cancel out the negative differences (scores below the mean). This property ensures that the total deviation from the mean is zero, reinforcing the concept that the mean represents the central tendency of the data.
The sum is the answer for adding and the difference is the answer for subtracting...
The sum of the differences between sample observations and the sample mean is always equal to zero. This is because the sample mean is calculated as the average of the observations, and when you subtract the mean from each observation, the positive and negative differences cancel each other out. Mathematically, this can be expressed as Σ(xi - x̄) = 0, where xi represents each individual observation and x̄ is the sample mean.
It means that it is an addition problem.
To find the sum of 8 numbers when the mean is 23, you can use the formula: sum = mean × number of values. In this case, the sum would be 23 × 8, which equals 184. Therefore, the sum of the 8 numbers is 184.
It means to add
Mean = (sum of the n numbers)/n
to find the mean of a set of numbers you have to find the total sum of the data divided by the number of addends in the data.
The mean sum of squares due to error: this is the sum of the squares of the differences between the observed values and the predicted values divided by the number of observations.
Add the digits together. The sum of the digits of 23 is 5.