Standard Deviation:
A standard deviation (or σ) is a measure of how dispersed the data is in relation to the mean. Low standard deviation means data are clustered around the mean, and high standard deviation indicates data are more spread out.

Variance:
The term variable refers to a statistical measure of the spread between numbers in a data set. More specifically, variance measures how far each number in the set is from the mean (average), and thus from every other number in the set. Variance is often depicted by this symbol: σ2.

Mean:
The mean is the mathematical average of a set of two or more numbers. The arithmetic mean and the geometric mean are two types of mean that can be calculated. The formula for calculating the arithmetic mean is to add up the numbers in a set and divide by the total quantity of numbers in the set.

Median:

The median is the middle number in a sorted, ascending or descending list of numbers and can be more descriptive of that data set than the average.

Range:

The range in statistics for a given data set is the difference between the highest and lowest values. For example, if the given data set is {2,5,8,10,3}, then the range will be 10 – 2 = 8. Thus, the range could also be defined as the difference between the highest observation and lowest observation.


What is continuous Data?

Key characteristics of continuous data are: Continuous data changes over time and can have different values at different time intervals. Continuous data is made up of random variables, which may or may not be whole numbers. Continuous data is measured using data analysis methods such as line graphs, skews, and so on.

What are discrete data?
Discrete data is a count that involves integers — only a limited number of values is possible. This type of data cannot be subdivided into different parts. Discrete data include discrete variables that are finite, numeric, countable, and non-negative integers.