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Can the variance be a negative number?
First, we compute the variance by taking the sum of squares and divide that by N which is the number of data points in the same. It is average squared deviation of each number from its mean. The point is a squared number is always positive and N is always positive so the variance must always be non-negative. ( It can be 0). The variance is a measure of the dispersion of a set of data points around their mean value. It would not make sense for it to be negative.
Is variance square of standard deviation?
Yes, the variance of a data set is the square of the standard deviation (sigma) of the set. This means that the variance is always a positive number, even though the data might have a negative sigma value.
What is the smallest measure of central tendency in a positively skewed distribution?
If the distribution is positively skewed distribution, the mean will always be the highest estimate of central tendency and the mode will always be the lowest estimate of central tendency. This is true if we assume the distribution has a single mode.
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.
What The sum of two decimals greater than 0.5 is always greater than 1?
The sum of two decimal numbers greater than 0.5 will always be greater than 1
For the normal distribution does it always require a continuity correction?
Use the continuity correction when using the normal distribution to approximate a binomial distribution to take into account the binomial is a discrete distribution and the normal distribution is continuous.
In the standard normal distribution the variance is always 1?
true
If the mean of a normal distribution is negative what is the varience?
The variance is always positive. The variance is not directly related to the sign (nor magnitude) of the mean.
How the symmetric distribution is always normal?
The statement is false. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.
Can the variance of a normally distributed random variable be negative?
No. The variance of any distribution is the sum of the squares of the deviation from the mean. Since the square of the deviation is essentially the square of the absolute value of the deviation, that means the variance is always positive, be the distribution normal, poisson, or other.
Is it true that the variance of z is always greater than 2?
z can be any number
What does probalility distribution mean?
In parametric statistical analysis we always have some probability distributions such as Normal, Binomial, Poisson uniform etc.In statistics we always work with data. So Probability distribution means "from which distribution the data are?
What is importance of central limit theorem?
The importance is that the sum of a large number of independent random variables is always approximately normally distributed as long as each random variable has the same distribution and that distribution has a finite mean and variance. The point is that it DOES NOT matter what the particular distribution is. So whatever distribution you start with, you always end up with normal.
Why the standard deviation of a set of data will always be greater than or equal to 0?
Because it is defined as the principal square root of the variance.
Distinguish between mean deviation and standard deviation?
The mean deviation for any distribution is always 0 and so conveys no information whatsoever. The standard deviation is the square root of the variance. The variance of a set of values is the sum of the probability of each value multiplied by the square of its difference from the mean for the set. A simpler way to calculate the variance is Expected value of squares - Square of Expected value.
Can additive variance have a negative value?
No. Variance is always positive and so the sum of variances must also be positive.
The sample variance is always smaller than the true value of the population variance is always larger than the true value of the population variance could be smaller equal to or?
yes, it can be smaller, equal or larger to the true value of the population varience.
