Information is not sufficient to find mean deviation and standard deviation.
Mean 0, standard deviation 1.
Mean = 0 Standard Deviation = 1
Standard deviation is the variance from the mean of the data.
Standard deviation can be greater than the mean.
Standard error of the mean (SEM) and standard deviation of the mean is the same thing. However, standard deviation is not the same as the SEM. To obtain SEM from the standard deviation, divide the standard deviation by the square root of the sample size.
Standard deviation is a measure of variation from the mean of a data set. 1 standard deviation from the mean (which is usually + and - from mean) contains 68% of the data.
No. A small standard deviation with a large mean will yield points further from the mean than a large standard deviation of a small mean. Standard deviation is best thought of as spread or dispersion.
Yes. Consider the definition of the standard deviation. It is the square root of the variance from the mean. As a result, it can be said that the standard deviation is dependent on the mean.
You cannot because the standard deviation is not related to the median.
The standard deviation tells us nothing about the mean.
The mean is the average value and the standard deviation is the variation from the mean value.
no the standard deviation is not equal to mean of absolute distance from the mean
There is 1) standard deviation, 2) mean deviation and 3) mean absolute deviation. The standard deviation is calculated most of the time. If our objective is to estimate the variance of the overall population from a representative random sample, then it has been shown theoretically that the standard deviation is the best estimate (most efficient). The mean deviation is calculated by first calculating the mean of the data and then calculating the deviation (value - mean) for each value. If we then sum these deviations, we calculate the mean deviation which will always be zero. So this statistic has little value. The individual deviations may however be of interest. See related link. To obtain the means absolute deviation (MAD), we sum the absolute value of the individual deviations. We will obtain a value that is similar to the standard deviation, a measure of dispersal of the data values. The MAD may be transformed to a standard deviation, if the distribution is known. The MAD has been shown to be less efficient in estimating the standard deviation, but a more robust estimator (not as influenced by erroneous data) as the standard deviation. See related link. Most of the time we use the standard deviation to provide the best estimate of the variance of the population.
The mean is "pushed" in the direction of the outlier. The standard deviation increases.
In general, a mean can be greater or less than the standard deviation.
No. The average of the deviations, or mean deviation, will always be zero. The standard deviation is the average squared deviation which is usually non-zero.
16.5 is 1 standard deviation from the mean. If you add the mean of 14 to the 1 standard deviation of 2.5, the result is 16.5.
If repeated samples are taken from a population, then they will not have the same mean each time. The mean itself will have some distribution. This will have the same mean as the population mean and the standard deviation of this statistic is the standard deviation of the mean.
Standard deviation describes the spread of a distribution around its mean.
the standard deviation
Standard deviation is how much a group deviates from the whole. In order to calculate standard deviation, you must know the mean.
It does not indicate anything if the mean is greater than the standard deviation.
Yes it does. The center, which is the mean, affects the standard deviation in a potisive way. The higher the mean is, the bigger the standard deviation.
B because the spread, in this case standard deviation, is larger.