Respuesta :
Lets make a table first.
x P(x)
-----------------------------
0 0.07
1 0.68
2 0.21
3 0.03
4 0.01
Mean = Expected value[E(X)] = [tex] \sum\limits^4_0 {x} \, P(x)[/tex]
= 0(0.07)+1(0.68)+2(0.21)+3(0.03)+4(0.01)
= 1.23
Variance[V(X)] = E(X²) - [E(X)]²
E(X²) = [tex] \sum\limits^4_0 {x^{2} } \, P(x)[/tex]
= 0²(0.07)+1²(0.68)+2²(0.21)+3²(0.03)+4²(0.01)
= 1.95
Therefore,
V(X) = E(X²)-[E(X)]² = 1.95-1.23² = 0.4371
Standard deviation(σ) = √V(X) = √0.4371 = 0.66
x P(x)
-----------------------------
0 0.07
1 0.68
2 0.21
3 0.03
4 0.01
Mean = Expected value[E(X)] = [tex] \sum\limits^4_0 {x} \, P(x)[/tex]
= 0(0.07)+1(0.68)+2(0.21)+3(0.03)+4(0.01)
= 1.23
Variance[V(X)] = E(X²) - [E(X)]²
E(X²) = [tex] \sum\limits^4_0 {x^{2} } \, P(x)[/tex]
= 0²(0.07)+1²(0.68)+2²(0.21)+3²(0.03)+4²(0.01)
= 1.95
Therefore,
V(X) = E(X²)-[E(X)]² = 1.95-1.23² = 0.4371
Standard deviation(σ) = √V(X) = √0.4371 = 0.66
The Mean and standard deviation of the given dataset come to be 1.23 and 0.66 respectively.
What is the standard deviation?
The standard deviation of a random variable, sample, statistical population, data set, or probability distribution is the square root of its variance.
x P(x) xP(x) x² x² P(x)
0 0.07 0 0 0
1 0.68 0.68 1 0.68
2 0.21 0.42 4 0.84
3 0.03 0.09 9 0.27
4 0.01 0.04 16 0.16
ΣxP(x) = 1.23
So, Mean = 1.23
Σx² P(x) =1.95
(ΣxP(x))² = 1.23² = 1.513
So, Variance = Σx² P(x) - (ΣxP(x))²
Variance = 1.95 - 1.513
Variance = 0.437
Standard deviation =√variance
Standard deviation =√0.437
Standard deviation = 0.66
Therefore, the Mean and standard deviation of the given dataset come to be 1.23 and 0.66 respectively.
To get more about standard deviation visit:
https://brainly.com/question/475676