Which one is the correct formula for variance?

Correct option is B

​$$\text{(c) Variance} = \frac{\sum (X - \bar{X})^2}{N^2}$$​​

-X is an individual data point,
-Xˉ\bar{X} is the mean of the data,
-N is the number of data points,
$$\sum (X - \bar{X})^2$$​represents the sum of squared differences between each data point and the mean.
This formula computes the average squared deviation from the mean, which is what variance measures. The standard deviation is simply the square root of the variance.

Information Booster:
Variance is a measure of how far data points are spread out from the mean.
Variance is expressed in squared units of the original data, which can make interpretation less intuitive. The standard deviation is often used to express variability in the original units.
The formula for variance assumes that the data represents the entire population. If you are working with a sample, a slightly adjusted formula is used, where the denominator is N−1 instead of N.
Variance is useful in many statistical analyses, such as in ANOVA, regression analysis, and quality control.
The value of variance increases as the spread of data points increases, and it approaches zero as the data points become more concentrated around the mean.