It is a measure of how variable the data is. The average distance from the average.
The standard deviation.
The mean average deviation is the same as the mean deviation (or the average deviation) and they are, by definition, 0.
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 standard deviation of a distribution is the average spread from the mean (average). If I told you I had a distribution of data with average 10000 and standard deviation 10, you'd know that most of the data is close to the middle. If I told you I had a distrubtion of data with average 10000 and standard deviation 3000, you'd know that the data in this distribution is much more spread out. dhaussling@gmail.com
The Mean Absolute Deviation indicates how clustered (close together) the data is, i also indicates the average of the distance of the values and the mean.
The average mean absolute deviation of a data set is the average of the absolute deviations from a central point. It is a summary statistic of statistical dispersion or variability.
It is the average of the distances between the data plots and the mean of the set.
The average deviation is always 0.
This means that the set of data is clustered really close to the mean/average. Your data set likely has a small range (highest value - lowest value). In other words, if the average is 6.3, and the standard deviation is 0.7, this means that each individual piece of data, on average, is different from the mean by 0.7. Each piece of data deviates from the mean by an average (standard) of 0.7; hence standard deviation! By definition, 66% of all data is 1 standard deviation from the mean, so 66% of the data in this example would be between the values of 5.6 and 7.0.
Yes, depending on the data being studied. Standard deviation can be thought of as the magnitude of the average distance between the data points and their mean.
Standard deviation in statistics refers to how much deviation there is from the average or mean value. Sample deviation refers to the data that was collected from a smaller pool than the population.