What does the mean and standard deviation tell us?
Standard deviation is a number used to tell how measurements for a group are spread out from the average (mean), or expected value. A low standard deviation means that most of the numbers are very close to the average. A high standard deviation means that the numbers are spread out.
The standard deviation is simply the square root of the variance. The average deviation, also called the mean absolute deviation, is another measure of variability. However, average deviation utilizes absolute values instead of squares to circumvent the issue of negative differences between data and the mean.
- The average of these numbers (6 ÷ 5) is 1.2 which is the mean deviation. Also called mean absolute deviation, it is used as a measure of dispersion where the number of values or quantities is small, otherwise standard deviation is used.
- In statistics, the 68–95–99.7 rule is a shorthand used to remember the percentage of values that lie within a band around the mean in a normal distribution with a width of two, four and six standard deviations, respectively; more accurately, 68.27%, 95.45% and 99.73% of the values lie within one, two and three standard
- The Normal Curve tells us that numerical data will be distributed in a pattern around an average (the center line). Standard deviation is considered the most useful index of variability. It is a single number that tells us the variability, or spread, of a distribution (group of scores).
The Standard Deviation is a measure of how spread out numbers are. Its symbol is σ (the greek letter sigma) The formula is easy: it is the square root of the Variance.
- For a given data set, the standard deviation measures how spread out numbers are from an average value. Standard deviation can be calculated by taking the square root of the variance, which itself is the average of the squared differences of the mean.
- The variance (symbolized by S2) and standard deviation (the square root of the variance, symbolized by S) are the most commonly used measures of spread. We know that variance is a measure of how spread out a data set is. It is calculated as the average squared deviation of each number from the mean of a data set.
- By convention, specific symbols represent certain sample statistics. For example, x refers to a sample mean. s refers to the standard deviation of a sample. s2 refers to the variance of a sample.
Updated: 2nd October 2019