"Analyzing Standard Deviation in Data Analysis"
Standard Deviation in simple terms can be defined as a measure to tell how measurements in a group are spread out from the average (mean).
- A low standard deviation means that most of the numbers are close to the average.
- A high standard deviation means that the numbers are more spread out.
Let's again go back to the same 2 examples we discussed in article "Interpreting Mean \ Median in Data Analysis", link given below.
Example 1:- Student data
Descriptive Statistics:-
As seen above the standard deviation for class B is lower than class A, hence we can interpret student in class B have given a consistent performance, as compared to students in Class A. Since data points for Class B are more tightly coupled to mean.
In example above Standard Deviation is expressed as marks.
Example 2:- Stock data
Normalized data:-
Descriptive Statistics (normalized data) :-
Since standard deviation for both companies is same, it can be interpreted that both companies have given consistent performance in last 1 month.
In example above Standard Deviation is expressed as price in dollars AUD (Australian Dollars) same as base data.
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