\(2\)
\(10\)
\(18\)
\(16\)
\(20\)
Given data:
Let, the Co-efficient of variation of 1st data = \(CV_1=50\)
Let, the Co-efficient of variation of 2nd data = \(CV_2=75\)
and Variance \((σ_1^{2})=25\) . So, \( σ_1=5\)
Variance \((σ_2^{2})=36\) . So, \( σ_1=6\)
We know that,
\(CV_1=\dfrac{σ_1}{x_1} × 100\)
\(⇒ x_1=\dfrac{5}{CV_1} × 100\)
\(⇒ x_1=\dfrac{5}{50} × 100\)
\(⇒ x_1=10\)
Similarly solving for 2nd data we get
\(⇒x_2=8\)
Hence , \(x_1+x_2=10+8=18\) (_Ans.)
According to layman’s words, the variance is a measure of how far a set of data are dispersed out from their mean or average value. It is denoted as ‘σ2’.
Read More: Difference Between Variance and Standard Deviation
The spread of statistical data is measured by the standard deviation. Distribution measures the deviation of data from its mean or average position. The degree of dispersion is computed by the method of estimating the deviation of data points. It is denoted by the symbol, ‘σ’.
1. Population Standard Deviation
2. Sample Standard Deviation