What's the unusual west pointing M in Standard Deviation Terms?

What type of risk is measured by standard deviation?

In terms of stock analysis, volatility.

Why variance is bigger than standard deviation?

The variance is standard deviation squared, or, in other terms, the standard deviation is the square root of the variance. In many cases, this means that the variance is bigger than the standard deviation - but not always, it depends on the specific values.

If the standard deviation decreases does the mean decrease?

Not necessarily. The standard deviation measures (in simplified terms) how different the numbers are from each other, while the mean is their average. If the standard deviation decreases, it means the numbers are closer to each other, it doesn't change how big the numbers are.

What is a 1.66 standard deviation in percentage?

The standard deviation is a measure of spread in a distribution, and 1.66 sd is a measure of a multiple of that interval. What that represents, in percentage terms, depends on the distribution, and whether the 1.66 sd is on one side of the mean or both. In view of the missing information, there can be no simple answer.

In a standard normal distribution what is the value of the mean and standard deviation?

idk about normal distribution but for Mean "M" = (overall sum of "x") / "n" frequency distribution: 'M' = Overall sum of (' x ' * ' f ') / overall sum of ( ' f ' ) M = Mean x = Mid Point f = frequiency n = number of variables ALL FOR STANDARD DEVIATION * * * * * A general Normal distribution is usually described in terms of its parameters, and given as N(mu, sigma2) where mu is the mean and sigma is the standard deviation. The STANDARD Normal distribution is the N(0, 1) distribution, that is, it has mean = 0 and variance (or standard deviation) = 1.

What is the relationship between the mean and standard deviation in statistics?

The 'standard deviation' in statistics or probability is a measure of how spread out the numbers are. It mathematical terms, it is the square root of the mean of the squared deviations of all the numbers in the data set from the mean of that set. It is approximately equal to the average deviation from the mean. If you have a set of values with low standard deviation, it means that in general, most of the values are close to the mean. A high standard deviation means that the values in general, differ a lot from the mean. The variance is the standard deviation squared. That is to say, the standard deviation is the square root of the variance. To calculate the variance, we simply take each number in the set and subtract it from the mean. Next square that value and do the same for each number in the set. Lastly, take the mean of all the squares. The mean of the squared deviation from the mean is the variance. The square root of the variance is the standard deviation. If you take the following data series for example, the mean for all of them is '3'. 3, 3, 3, 3, 3, 3 all the values are 3, they're the same as the mean. The standard deviation is zero. This is because the difference from the mean is zero in each case, and after squaring and then taking the mean, the variance is zero. Last, the square root of zero is zero so the standard deviation is zero. Of note is that since you are squaring the deviations from the mean, the variance and hence the standard deviation can never be negative. 1, 3, 3, 3, 3, 5 - most of the values are the same as the mean. This has a low standard deviation. In this case, the standard deviation is very small since most of the difference from the mean are small. 1, 1, 1, 5, 5, 5 - all the values are two higher or two lower than the mean. This series has the highest standard deviation.

Is the coefficient of variation a better measure of risk than the standard deviation if the expected returns of the securities being compared differ significantly?

The Standard deviation is an absolute measure of risk while the coefficent of variation is a relative measure. The coefficent is more useful when using it in terms of more than one investment. The reason being that they have different returns on average which means the standard deviation may understate the actual risk or overstate depending.

How can you find error limit?

The error in a set of observations is usually expressed in terms of the Standard Deviation of the measurement set. This implies that for a given plotted point, you have several measurements.

What does downgoing mean in medical terms?

Downgoing in medical terms means pointing downward. The signficance of pointing downward will differ depending on context.

What does it means if the standard deviation is small?

Simplest terms, it means that the sample values are grouped closely together. Another way of saying it is that the range of values is small. The plot will be a leptokurtic plot (peaked).

What does mean absolute deviation mean in math terms?

it means bobo pooped

What is the purpose of mean absolute deviation?

Various answers to this question are possible.The mean absolute deviation (MAD) is a measure of the dispersion or spread of a sample or a population. So one of its purposes is as a measure.As such it's an alternative to the standard deviation that is said to be more robust in the sense that the sample MAD can be used to provide more accurate estimates of the population dispersion because it is less sensitive to outliers.Beyond this, some distributions that have no standard deviations do have MADs; for example, the Cauchy. This means that the dispersions of virtually all distributions can be compared in terms of their MADs.Please see the link.