We have to use the formula for standard deviation of a probability distribution:
[tex]\sigma=\sqrt[]{\sum^{}_{i\mathop=0}(x_i-\mu)^2\cdot P(x_i)}[/tex]
x P(x) x*P(x) (xi - μ)^2*P(x)
0 0.11 0 0.180
1 0.64 0.64 0.050
2 0.13 0.26 0.067
3 0.1 0.3 0.296
4 0.02 0.08 0.148
The expected value μ would be the sum of the values of the third column of the table.
Therefore μ = 1.28
The sum of the values of the fourth column would be: 0.7416
Taking the square root of the last value, we have: 0.861
The answer is option D
