44.9
The standard deviation tells us nothing about the mean.
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.
It means that the data are spread out around their central value.
1.41
By the definition of standard deviation, 95.46% of the normal population will be within 2 SD of the mean. Explanation: The normal distribution of a population means it follows the "bell curve". The center of this bell curve is the population's mean value. One standard deviation defines two areas (on the left and right side of the central "mean" value) under the bell curve that each have 34.13% of the population. The next standard deviation adds two additional areas under the curve, each having 13.6% of the population. Adding the areas under the curves on both sides gives us (34.13% + 13.6%) x 2 = 95.46%
US IQ standard Deviation is 16.
The standard deviation tells us nothing about the mean.
The standard deviation of height in the US population is approximately 3 inches.
standard deviation is the square roots of variance, a measure of spread or variability of data . it is given by (variance)^1/2
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 variation of a set of numbrs
All US Vice Presidents are not yet dead.
Standard deviation measures the dispersion or variability of a dataset by quantifying how much individual data points deviate from the mean. A low standard deviation indicates that the data points are clustered closely around the mean, while a high standard deviation signifies that they are spread out over a wider range. This statistic helps in understanding the consistency of the data and is crucial for interpreting the reliability of statistical analyses.
It gives us an idea how far away we are from the center of a normal distribution.
It means that the data are spread out around their central value.
Standard deviation measures the dispersion or variability of data points around the mean. A low standard deviation indicates that the data points are closely clustered around the mean, suggesting that the mean is a reliable representation of the dataset. Conversely, a high standard deviation signifies greater variability, which may diminish the mean’s usefulness as a summary statistic, as it may not accurately reflect the data's central tendency. Thus, understanding standard deviation helps assess how well the mean represents the underlying data.
zero