The answer depends on greater standard deviation that WHAT!
It is a measure of the spread of the distribution. The greater the standard deviation the more variety there is in the observations.
It is the value that is one standard deviation greater than the mean of a Normal (Gaussian) distribution.
The standard deviation must be greater than or equal to zero.
In general, a mean can be greater or less than the standard deviation.
Yes. Since the standard deviation is defined as the square root of the variance, it can be said that the higher the standard deviation, the higher the variance.
It is a measure of the spread of the distribution. The greater the standard deviation the more variety there is in the observations.
Yes - but the distribution is not a normal distribution - this can happen with a distribution that has a very long tail.
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.
Standard deviation can be greater than the mean.
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.
It is the value that is one standard deviation greater than the mean of a Normal (Gaussian) distribution.
It does not indicate anything if the mean is greater than the standard deviation.
The standard deviation must be greater than or equal to zero.
In general, a mean can be greater or less than the standard deviation.
Yes. Since the standard deviation is defined as the square root of the variance, it can be said that the higher the standard deviation, the higher the variance.
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The width of the peak of a normal curve depends primarily on the standard deviation of the distribution. A larger standard deviation results in a wider and flatter curve, indicating greater variability in the data, while a smaller standard deviation yields a narrower and taller peak, indicating less variability. Thus, the standard deviation is crucial for determining the spread of the data around the mean.