It means that particular observation is close to the population [or sample] mean.
ask your mom they know more than u
You cannot. If you are told the standard deviation of a variable there is no way to tell whether that was derived from grouped or ungrouped data.
The smaller the standard deviation, the closer together the data is. A standard deviation of 0 tells you that every number is the same.
Mean deviation, standard deviation, and variance are measures of dispersion that indicate how spread out the values in a dataset are around the mean. Mean deviation calculates the average of absolute deviations from the mean, while variance measures the average of squared deviations, providing a sense of variability in squared units. Standard deviation is the square root of variance, expressing dispersion in the same units as the data. Together, these metrics help assess the reliability and variability of data, which is crucial for statistical analysis and decision-making.
Standard deviation is a statistical measure that quantifies the amount of variation or dispersion in a set of data values. A low standard deviation indicates that the data points are clustered closely around the mean, while a high standard deviation signifies that the data points are spread out over a wider range of values. It helps in understanding the consistency or variability of the data, which is crucial for making informed decisions based on that data.
i dont know...... it means
It is a measure of the spread or dispersion of the data.
ask your mom they know more than u
it tells you
You cannot. If you are told the standard deviation of a variable there is no way to tell whether that was derived from grouped or ungrouped data.
The smaller the standard deviation, the closer together the data is. A standard deviation of 0 tells you that every number is the same.
Mean deviation, standard deviation, and variance are measures of dispersion that indicate how spread out the values in a dataset are around the mean. Mean deviation calculates the average of absolute deviations from the mean, while variance measures the average of squared deviations, providing a sense of variability in squared units. Standard deviation is the square root of variance, expressing dispersion in the same units as the data. Together, these metrics help assess the reliability and variability of data, which is crucial for statistical analysis and decision-making.
The mean and standard deviation often go together because they both describe different but complementary things about a distribution of data. The mean can tell you where the center of the distribution is and the standard deviation can tell you how much the data is spread around the mean.
It tells you how much variability there is in the data. A small standard deviation (SD) shows that the data are all very close to the mean whereas a large SD indicates a lot of variability around the mean. Of course, the variability, as measured by the SD, can be reduced simply by using a larger measurement scale!
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 is a statistical measure that quantifies the amount of variation or dispersion in a set of data values. A low standard deviation indicates that the data points are clustered closely around the mean, while a high standard deviation signifies that the data points are spread out over a wider range of values. It helps in understanding the consistency or variability of the data, which is crucial for making informed decisions based on that data.
It means that the data are spread out around their central value.