Question

Find u if p = [x•P(x)]. Then, find o if o2 = {[x• P(x)] –H2 X P(x) 0 0.0005 1 0.0091 2 0.0648 3 0.2297 4 0.4072 5 0.2887 (Sim

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Answer #1
X P(X)   
0 0.0005
1 0.0091
2 0.0648
3 0.2297
4 0.4072
5 0.2887

Now, we need to multiply the corresponding X outcomes with the corresponding probabilities, in order to compute the population mean μ:

X    p(X) X⋅p(X)
0 0.0005 0⋅0.0005=0
1 0.0091 1⋅0.0091=0.0091
2 0.0648 2⋅0.0648=0.1296
3 0.2297 3⋅0.2297=0.6891
4 0.4072 4⋅0.4072=1.6288
5 0.2887 5⋅0.2887=1.4435

Therefore, the population mean is calculated as follows:

\begin{array}{ccl} \mu & = & \sum_{i=1}^{n} X_i p(X_i) \\ \\ & = & \displaystyle 0\cdot 0.0005+1\cdot 0.0091+2\cdot 0.0648+3\cdot 0.2297+4\cdot 0.4072+5\cdot 0.2887 \\ \\ & = & \displaystyle 3.9001 \end{array}

Now, we need to multiply the corresponding squares X^2 of the outcomes with the corresponding probabilities, in order to compute the population variance \sigma^2 :

X p(X)    X⋅p(X) X^2⋅p(X)
0 0.0005 0⋅0.0005=0 0^2 \cdot 0.0005 = 0
1 0.0091 1⋅0.0091=0.0091 1^2 \cdot 0.0091 = 0.0091
2 0.0648 2⋅0.0648=0.1296 2^2 \cdot 0.0648 = 0.2592
3 0.2297 3⋅0.2297=0.6891 3^2 \cdot 0.2297 = 2.0673
4 0.4072 4⋅0.4072=1.6288 4^2 \cdot 0.4072 = 6.5152
5 0.2887 5⋅0.2887=1.4435 5^2 \cdot 0.2887 = 7.2175

Therefore, we first compute the expected value of X^2 :

\begin{array}{ccl} E(X^2) & = & \sum_{i=1}^{n} X_i^2 p(X_i) \\ \\ & = & \displaystyle 0^2 \cdot 0.0005+1^2 \cdot 0.0091+2^2 \cdot 0.0648+3^2 \cdot 0.2297+4^2 \cdot 0.4072+5^2 \cdot 0.2887 \\ \\ & = & \displaystyle 16.0683 \end{array}

Therefore, the population variance is computed as follows:

\begin{array}{ccl} \sigma^2 &= & E(X^2) - E(X)^2 \\ \\ & = & \displaystyle 16.0683 - 3.9001^2 \\ \\ & = & \displaystyle 0.8575 \end{array}

And finally, taking square root to the variance we get that the population standard deviation is \sigma = \sqrt{ \sigma^2} = \sqrt{0.8575} = 0.926

Therefore, based on the discrete distribution, the population mean is μ=3.9001 and the population standard deviation is σ=0.926

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