We assume that the probabilities of getting heads and tails are the same
p = q = 1 2 p = q = \frac{1}{2} p = q = 2 1
Using the Bernoulli formula, we find the probabilities that there will be 0, 1, 2, 3 and 4 heads, respectively
P ( x = 0 ) = q 3 = 1 8 P\left( {x = 0} \right) = {q^3} = \frac{1}{{8}} P ( x = 0 ) = q 3 = 8 1
P ( x = 1 ) = C 3 1 p q 2 = 3 8 P(x = 1) = C_3^1p{q^2} = \frac{3}{{8}} P ( x = 1 ) = C 3 1 p q 2 = 8 3
P ( x = 2 ) = C 3 2 p 2 q = 3 8 P(x= 2) = C_3^2{p^2}{q} = \frac{3}{{8}} P ( x = 2 ) = C 3 2 p 2 q = 8 3
P ( x = 3 ) = p 3 = 1 8 P\left( {x = 3} \right) = {p^3} = \frac{1}{{8}} P ( x = 3 ) = p 3 = 8 1
We have a distribution series
So, the mean is
M ( x ) = ∑ x i p i = 0 ⋅ 1 + 1 ⋅ 3 + 2 ⋅ 3 + 3 ⋅ 1 8 = 12 8 = 3 2 M(x) = {\sum x _i}{p_i} = \frac{{0 \cdot 1 + 1 \cdot 3 + 2 \cdot 3 + 3 \cdot 1}}{8} = \frac{{12}}{8} = \frac{3}{2} M ( x ) = ∑ x i p i = 8 0 ⋅ 1 + 1 ⋅ 3 + 2 ⋅ 3 + 3 ⋅ 1 = 8 12 = 2 3
The variance is
V ( x ) = M ( x 2 ) − M 2 ( x ) = 0 ⋅ 1 + 1 ⋅ 3 + 4 ⋅ 3 + 9 ⋅ 1 8 − 9 4 = 3 4 V(x) = M\left( {{x^2}} \right) - {M^2}(x) = \frac{{0 \cdot 1 + 1 \cdot 3 + 4 \cdot 3 + 9 \cdot 1}}{8} - \frac{9}{4} = \frac{3}{4} V ( x ) = M ( x 2 ) − M 2 ( x ) = 8 0 ⋅ 1 + 1 ⋅ 3 + 4 ⋅ 3 + 9 ⋅ 1 − 4 9 = 4 3
standard deviation is
σ ( x ) = V ( x ) = 3 2 \sigma \left( x \right) = \sqrt {V(x)} = \frac{{\sqrt 3 }}{2} σ ( x ) = V ( x ) = 2 3
Answer: M ( x ) = 3 2 M(x) = \frac{3}{2} M ( x ) = 2 3 ; V ( x ) = 3 4 V(x) = \frac{3}{4} V ( x ) = 4 3 ; σ ( x ) = 3 2 \sigma \left( x \right) = \frac{{\sqrt 3 }}{2} σ ( x ) = 2 3
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