is the standard deviation a measure of the center or distribution...
my teacher told me center
i read the article
and i\'ve been lead to believe its a measure of the distribution not the center...
if it is a measure of the center how is it? I think it\'s a measure of the distribution...
Standard deviation is a measure of variation of scores. The measures of central tendency are the mean, mode and median.
I hope this helps. Thanks for asking.
Standard deviation is the measure of distribution. For example, it is the span between the least and greatest values of a data set. Hope this helps :)
The standard deviation is actually a measure of the dispersion or spread of a distribution, not the center. It quantifies how much the values in a dataset deviate from the mean. It provides information about how tightly or loosely the data points are clustered around the mean.
The measure of the center is typically represented by the mean or median, which represent the average or middle value of the dataset, respectively. These measures give an indication of the central tendency of the data.
In summary, the standard deviation is a measure of the distribution or spread of the data, while measures like mean or median represent the center or central tendency.
The standard deviation is actually a measure of the distribution, not the center. It quantifies the spread or variability of a set of data points. It tells us how much the data deviates or spreads out from the mean (average) value.
To understand why it's a measure of the distribution, let's take a look at how the standard deviation is calculated.
1. First, calculate the mean of the data set by summing up all the data points and dividing by the total number of points.
2. Then, find the difference between each individual data point and the mean. These differences are called deviations from the mean.
3. Square each deviation to get rid of any negative signs.
4. Average these squared deviations by summing them up and dividing by the total number of points. This average is called the variance.
5. Finally, take the square root of the variance to obtain the standard deviation.
The standard deviation summarizes how much the data points, on average, deviate from the mean. If the standard deviation is large, it means the data points are spread out widely from the mean, indicating a larger distribution. If the standard deviation is small, it means the data points are closer to the mean, resulting in a narrower distribution.
Therefore, the standard deviation provides information about the dispersion or distribution of the data, rather than the center.