Variance is basically the raw material of statistics. If you don't have variance (differences in scores) you don't have much to work with or for that matter you don't have much to talk or think about. Consider a test where everyone gets the same score. What does that tell you? You might have some measurement problem, wherein the test is so easy everyone aces it. Still it might be so hard that everyone gets a zero. Now consider two tests. On each everyone gets the same score. That is on test one everyone gets a 15 and on the second test everyone gets a 10. That isn't telling you much is it? Now these are extreme cases, but in general, more variance is better and less variance isn't so good.
There are many advantages and disadvantages of variance in statistics. One disadvantage is that you never know what answer you'll get.
It is the estimate of between-study variance, to quantify heterogeneity
The variance or standard deviation.
statistics first year paper in federal board is always become easy. if you repare only first 5 chapters with examples and definitions you will get 100 percent marks.. important things are summaries of chapter1 and 2.. mean,median,mode,variance,standard deviation,quartile deviation and moments...
There is a brief table in Mario Triola's Elementary Statistics text. In the 9th edition it is on pages 354 - 355 with an example.
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.
Explian DOE using Variance Analysis
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
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.
INFERENCES Any calculated number from a sample from the population is called a 'statistic', such as the mean or the variance.