\(243\)
\(81\)
\(729\)
\(9\)
\(733\)
Given that:
Standard deviation of \(x_1,x_2\) and \(x_3\) be .
The variance of random variables \(3x_1 + 4, 3x_2 + 4\), and \(3x_3 + 4,\) to be found ;
For a random variable \(X\) with standard deviation \(σ\) , the variance of a linear transformation\((aX + b)\), where \('a'\) and \('b'\) are constants and can be calculated as follows:
\(Var(aX + b) = a^2 × Var(X)\)
applying this to all three given variables we get;
For, \(3x_1 + 4: Var(3x_1 + 4)\)
\(= 3^2 × Var(x1) = 9 × 9 = 81\)
For, \(3x_2 + 4: Var(3x_2 + 4)\)
\(= 3^2 × Var(x_2) = 9 × 9 = 81\)
For, \(3x_3 + 4: Var(3x_3 + 4)\)
\(= 3^2 × Var(x3) = 9 × 9 = 81\)
Hence, the variance for the random variable is \(81\) for each of them.(_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