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Can the standard deviation or variance be negative?

No, a standard deviation or variance does not have a negative sign. The reason for this is that the deviations from the mean are squared in the formula. Deviations are squared to get rid of signs. In Absolute mean deviation, sum of the deviations is taken ignoring the signs, but there is no justification for doing so. (deviations are not squared here)


What does it mean normal distribution?

The Normal distribution is a probability distribution of the exponential family. It is a symmetric distribution which is defined by just two parameters: its mean and variance (or standard deviation. It is one of the most commonly occurring distributions for continuous variables. Also, under suitable conditions, other distributions can be approximated by the Normal. Unfortunately, these approximations are often used even if the required conditions are not met!


What is the square root of the average of the squared deviations from the mean?

It is the standard deviation.


What percent of data falls between 1 Standard deviation below and 2 stand deviations above the mean?

The answer will depend on what the distribution is. Non-statisticians often assum that the variable that they are interested in follows the Standard Normal distribution. This assumption must be justified. If that is the case then the answer is 81.9%


Is standard deviation the arithmetic mean of the squared deviations from the means?

No. Standard deviation is the square root of the mean of the squared deviations from the mean. Also, if the mean of the data is determined by the same process as the deviation from the mean, then you loose one degree of freedom, and the divisor in the calculation should be N-1, instead of just N.

Related Questions

What is the difference between t-distribution and standard normal distribution?

the t distributions take into account the variability of the sample standard deviations. I think that it is now common to use the t distribution when the population standard deviation is unknown, regardless of the sample size.


How do you find highest standard deviation in given number?

Standard deviations are measures of data distributions. Therefore, a single number cannot have meaningful standard deviation.


True or false two normal distributions that have the same mean are centered at the same place regardless of the relationship between their standard deviation?

True. Two normal distributions that have the same mean are centered at the same point on the horizontal axis, regardless of their standard deviations. The standard deviation affects the spread or width of the distributions, but it does not change their center location. Therefore, even with different standard deviations, the distributions will overlap at the mean.


How do you derive the mean deviation about the mean of the pareto type 1 distributions?

Easy. The mean deviation about the mean, for any distribution, MUST be 0.


Do some normal probability distributions have different means and different standard deviations?

Yes. Normal (or Gaussian) distribution are parametric distributions and they are defined by two parameters: the mean and the variance (square of standard deviation). Each pair of these parameters gives rise to a different normal distribution. However, they can all be "re-parametrised" to the standard normal distribution using z-transformations. The standard normal distribution has mean 0 and variance 1.


Why standard deviation is best measure of dispersion?

standard deviation is best measure of dispersion because all the data distributions are nearer to the normal distribution.


Why normality is required for standard deviation application?

Because the z-score table, which is heavily related to standard deviation, is only applicable to normal distributions.


Can the standard deviation or variance be negative?

No, a standard deviation or variance does not have a negative sign. The reason for this is that the deviations from the mean are squared in the formula. Deviations are squared to get rid of signs. In Absolute mean deviation, sum of the deviations is taken ignoring the signs, but there is no justification for doing so. (deviations are not squared here)


Difference between standard deviation and mean devition?

The mean deviation (also called the mean absolute deviation) is the mean of the absolute deviations of a set of data about the data's mean. The standard deviation sigma of a probability distribution is defined as the square root of the variance sigma^2,


What role do z scores play in this transformation of data from multiple distributions to standard normal distribution?

Z-scores standardize data from various distributions by transforming individual data points into a common scale based on their mean and standard deviation. This process involves subtracting the mean from each data point and dividing by the standard deviation, resulting in a distribution with a mean of 0 and a standard deviation of 1. This transformation enables comparisons across different datasets by converting them to the standard normal distribution, facilitating statistical analysis and interpretation.


What does standard deviation help you find?

Standard deviation helps you identify the relative level of variation from the mean or equation approximating the relationship in the data set. In a normal distribution 1 standard deviation left or right of the mean = 68.2% of the data 2 standard deviations left or right of the mean = 95.4% of the data 3 standard deviations left or right of the mean = 99.6% of the data


What happens in a normal distribution when the means are equal but the standard deviation changes?

The two distributions are symmetrical about the same point (the mean). The distribution where the sd is larger will be more flattened - with a lower peak and more spread out.