It does not indicate anything if the mean is greater than the standard deviation.
Standard deviation can be greater than the mean.
In general, a mean can be greater or less than the standard deviation.
In the same way that you calculate mean and median that are greater than the standard deviation!
Yes; the standard deviation is the square root of the mean, so it will always be larger.
Yes, the mean deviation is typically less than or equal to the standard deviation for a given dataset. The mean deviation measures the average absolute deviations from the mean, while the standard deviation takes into account the squared deviations, which can amplify the effect of outliers. Consequently, the standard deviation is usually greater than or equal to the mean deviation, but they can be equal in certain cases, such as when all data points are identical.
Information is not sufficient to find mean deviation and standard deviation.
No, standard deviation is not a point in a distribution; rather, it is a measure of the dispersion or spread of data points around the mean. It quantifies how much individual data points typically deviate from the mean value. A lower standard deviation indicates that the data points are closer to the mean, while a higher standard deviation indicates greater variability.
In a cube test for concrete, the standard deviation measures the variability of the compressive strength results from multiple samples. A low standard deviation indicates that the strength values are closely clustered around the mean, suggesting consistent quality and reliability of the concrete mix. Conversely, a high standard deviation reflects greater variability, which may indicate inconsistencies in the mix or potential weaknesses in the concrete. Thus, the standard deviation serves as a key indicator of the uniformity and strength of the concrete.
A standard normal distribution has a mean of zero and a standard deviation of 1. A normal distribution can have any real number as a mean and the standard deviation must be greater than zero.
Mean 0, standard deviation 1.
Mean = 0 Standard Deviation = 1
Let sigma = standard deviation. Standard error (of the sample mean) = sigma / square root of (n), where n is the sample size. Since you are dividing the standard deviation by a positive number greater than 1, the standard error is always smaller than the standard deviation.