A discrete random variable π has a cumulative probability distribution as shown below.
π = π¦ 0 1 2 3
π(π β€ π¦) 5π 10π 11π 12π
(a) Determine the value of π.
(b) Calculate expected value of π.
(c) Calculate variance and standard deviation of π.
(a) Find the value of k from the condition
"\\sum {{p_i}} = 1"
Then
"5k + 10k + 11k + 12k = 1 \\Rightarrow 38k = 1 \\Rightarrow k = \\frac{1}{{38}}"
The distribution series has the form
"\\begin{matrix}\ny&0&1&2&3\\\\\np&{\\frac{5}{{38}}}&{\\frac{{10}}{{38}}}&{\\frac{{11}}{{38}}}&{\\frac{{12}}{{38}}}\n\\end{matrix}"
Answer: "k = \\frac{1}{{38}}"
(b) "E(Y) = \\sum {{y_i}} {p_i} = \\frac{{0 \\cdot 5 + 1 \\cdot 10 + 2 \\cdot 11 + 3 \\cdot 12}}{{38}} = \\frac{{68}}{{38}} = \\frac{{34}}{{19}}"
Answer: "E(Y) = \\frac{{34}}{{19}}"
(c) Let's find the variance:
"D(Y) = M({Y^2}) - {M^2}\\left( Y \\right) = \\frac{{0 \\cdot 5 + 1 \\cdot 10 + 4 \\cdot 11 + 9 \\cdot 12}}{{38}} - {\\left( {\\frac{{34}}{{19}}} \\right)^2} = \\frac{{383}}{{361}}"
Then standard deviation is
"\\sigma \\left( Y \\right) = \\sqrt {D(Y)} = \\sqrt {\\frac{{383}}{{361}}} = \\frac{{\\sqrt {383} }}{{19}}"
Answer: "D(Y) = \\frac{{383}}{{361}}" ; "\\sigma \\left( Y \\right) = \\frac{{\\sqrt {383} }}{{19}}"
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