Variance is a measure of "relative to the mean, how far away does the other data fall" - it is a measure of dispersion. A high variance would indicate that your data is very much spread out over a large area (random), whereas a low variance would indicate that all your data is very similar.
Standard deviation (the square root of the variance) is a measure of "on average, how far away does the data fall from the mean". It can be interpreted in a similar way to the variance, but since it is square rooted, it is less susceptible to outliers.
In statistics, this is the symbol for the "Variance"
Since this is regarding statistics I assume you mean lower case sigma (σ) which, in statistics, is the symbol used for standard deviation, and σ2 is known as the variance.
They are measures of the spread of the data and constitute one of the key descriptive statistics.
INFERENCES Any calculated number from a sample from the population is called a 'statistic', such as the mean or the variance.
actual budget/budget = variance%
In statistics, this is the symbol for the "Variance"
There are many advantages and disadvantages of variance in statistics. One disadvantage is that you never know what answer you'll get.
The variance is: 0.666666666667
In statistics, variance measures how far apart a set of numbers is spread out. If the numbers are identical, the variance is zero. Variance can never be negative.
Since this is regarding statistics I assume you mean lower case sigma (σ) which, in statistics, is the symbol used for standard deviation, and σ2 is known as the variance.
They are measures of the spread of the data and constitute one of the key descriptive statistics.
Relevant statistics contain data that directly answers the question researchers analyzed. Findings include samples with standard deviation, distribution, and variance included.
It is the estimate of between-study variance, to quantify heterogeneity
William C. Guenther has written: 'A sample size formula for the hypergeometric' -- subject(s): Hypergeometric distribution, Sampling (Statistics) 'Concepts of probability' -- subject(s): Probabilities 'A sample size formula for a non-central t test' -- subject(s): Sampling (Statistics), Statistical hypothesis testing, T-test (Statistics) 'Analysis of variance' -- subject(s): Analysis of variance
INFERENCES Any calculated number from a sample from the population is called a 'statistic', such as the mean or the variance.
John W. Tukey has written: 'Lecture notes on analysis of variance' -- subject(s): Mathematical statistics
Practical significance in statistics is concern with whether the acquired research result is useful in the real world verus in theory which is not practical.