The answer depends on the degrees of freedom (df). If the df > 1 then the mean is 0, and the standard deviation, for df > 2, is sqrt[df/(df - 2)].
T score is usually used when the sample size is below 30 and/or when the population standard deviation is unknown.
68% of the scores are within 1 standard deviation of the mean -80, 120 95% of the scores are within 2 standard deviations of the mean -60, 140 99.7% of the scores are within 3 standard deviations of the mean -40, 180
The standard deviation for the Woodcock-Johnson III Tests of Achievement is typically set at 15. This is consistent with many standardized tests, which use a mean of 100 and a standard deviation of 15 to represent scores on a normal distribution. This allows for the interpretation of individual test scores in relation to the broader population.
78
No, it is called the absolute deviation.
This question cannot be answered unless the bowling scores are provided.
If the standard deviation of 10 scores is zero, then all scores are the same.
All the scores are equal
mean
A variable that has been transformed by multiplication of all scores by a constant and/or by the addition of a constant to all scores. Often these constants are selected so that the transformed scores have a mean of zero and a variance (and standard deviation) of 1.0.
Since the standard deviation is zero, the scores are all the same. And, since their mean is 10, they must all be 10.
Standard Deviation tells you how spread out the set of scores are with respects to the mean. It measures the variability of the data. A small standard deviation implies that the data is close to the mean/average (+ or - a small range); the larger the standard deviation the more dispersed the data is from the mean.
The answer depends on the degrees of freedom (df). If the df > 1 then the mean is 0, and the standard deviation, for df > 2, is sqrt[df/(df - 2)].
Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller. Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller. Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller. Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller.
The standard deviation is defined as the square root of the variance, so the variance is the same as the squared standard deviation.
It is not. And that is because the mean deviation of ANY variable is 0 and you cannot divide by 0.