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Q: What will the sum of the deviation score always be?
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What The sum of the difference of score around the mean is?

The sum of the differences between each score and the mean is always zero. This is because the mean is the "center" of the data and any deviation from the mean in one direction is offset by an equal deviation in the opposite direction. This property is essential in understanding the concept of the mean as a measure of central tendency.


What is the Sum of deviation from the mean is?

The sum of deviations from the mean, for any set of numbers, is always zero. For this reason it is quite useless.


What is the deviation of 28 63 50 53 36 40?

It depends on what the deviation is from. Also, the sum of the deviations from any fixed number will always be zero.


Can the sum of squared deviation have a value of less than zero?

No. The square of a number is always positive, so the sum of several of them must also be positive.


What is the sum of all deviations of a data value from a measure of central location that will always be zero?

Difference (deviation) from the mean.


Which measure of central location will the sum of the deviation of each value from the data's average will always be zero?

the mean %100


What is the z value for an IQ score of 100?

IQ is distributed normally, with a mean of 100 and a standard deviation of 15. The z-score of 100 is therefore:(value-mean)*standard deviation= (100-100)*15= 0More generally, a raw score that is equivalent to the mean of a normal distribution will always have a z-score of 0.


Calculate a deviation score?

27


What is the sum of squared deviation?

The variance.


Which is better a score of 92 on a test with a mean of 71 and a standard deviation of 15 or a score of 688 on a test with a mean of 493 and a standard deviation of 150?

score of 92


Why use the T score?

T-score is used when you don't have the population standard deviation and must use the sample standard deviation as a substitute.


Can the variance of a normally distributed random variable be negative?

No. The variance of any distribution is the sum of the squares of the deviation from the mean. Since the square of the deviation is essentially the square of the absolute value of the deviation, that means the variance is always positive, be the distribution normal, poisson, or other.