Questions: Two tire-quality experts examine stacks of tires and assign a quality rating to each tire on a 3-point scale. Let X denote the rating given by expert A and Y denote the rating given by expert B. The following table gives the joint distribution for X and Y. Find μX and μY Joint Distribution f(x, y) y 1 2 3 x 1 0.12 0.06 0.01 2 0.11 0.32 0.06 3 0.02 0.11 0.19

Two tire-quality experts examine stacks of tires and assign a quality rating to each tire on a 3-point scale. Let X denote the rating given by expert A and Y denote the rating given by expert B. The following table gives the joint distribution for X and Y. Find μX and μY

Joint Distribution

f(x, y)        y
              1     2     3
x     1     0.12  0.06  0.01
       2     0.11  0.32  0.06
       3     0.02  0.11  0.19
Transcript text: Two tire-quality experts examine stacks of tires and assign a quality rating to each tire on a 3-point scale. Let $X$ denote the rating given by expert $A$ and $Y$ denote the rating given by expert $B$. The following table gives the joint distribution for $X$ and $Y$. Find $\mu_{X}$ and $\mu_{Y}$ Joint Distribution \begin{tabular}{|c|c|c|c|c|c|} \hline \multirow{2}{*}{\multicolumn{2}{|c|}{$f(x, y)$}} & & $y$ & & \\ \hline & & 1 & 2 & 3 & \\ \hline \multirow{3}{*}{ x } & 1 & 0.12 & 0.06 & 0.01 & \\ \hline & 2 & 0.11 & 0.32 & 0.06 & \\ \hline & 3 & 0.02 & 0.11 & 0.19 & \\ \hline \end{tabular}
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Solution

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Solution Steps

To find the expected values (means) μX\mu_X and μY\mu_Y, we need to use the joint distribution table. The expected value of a random variable is calculated by summing the product of each value and its probability.

For μX\mu_X, we sum over all possible values of XX weighted by their marginal probabilities. Similarly, for μY\mu_Y, we sum over all possible values of YY weighted by their marginal probabilities.

Step 1: Calculate Marginal Probabilities for XX

To find the marginal probabilities for XX, we sum the joint probabilities over all values of YY: P(X=1)=0.12+0.06+0.01=0.19 P(X=1) = 0.12 + 0.06 + 0.01 = 0.19 P(X=2)=0.11+0.32+0.06=0.49 P(X=2) = 0.11 + 0.32 + 0.06 = 0.49 P(X=3)=0.02+0.11+0.19=0.32 P(X=3) = 0.02 + 0.11 + 0.19 = 0.32

Step 2: Calculate Marginal Probabilities for YY

To find the marginal probabilities for YY, we sum the joint probabilities over all values of XX: P(Y=1)=0.12+0.11+0.02=0.25 P(Y=1) = 0.12 + 0.11 + 0.02 = 0.25 P(Y=2)=0.06+0.32+0.11=0.49 P(Y=2) = 0.06 + 0.32 + 0.11 = 0.49 P(Y=3)=0.01+0.06+0.19=0.26 P(Y=3) = 0.01 + 0.06 + 0.19 = 0.26

Step 3: Calculate Expected Value μX\mu_X

The expected value μX\mu_X is calculated by summing the product of each value of XX and its marginal probability: μX=10.19+20.49+30.32=0.19+0.98+0.96=2.13 \mu_X = 1 \cdot 0.19 + 2 \cdot 0.49 + 3 \cdot 0.32 = 0.19 + 0.98 + 0.96 = 2.13

Step 4: Calculate Expected Value μY\mu_Y

The expected value μY\mu_Y is calculated by summing the product of each value of YY and its marginal probability: μY=10.25+20.49+30.26=0.25+0.98+0.78=2.01 \mu_Y = 1 \cdot 0.25 + 2 \cdot 0.49 + 3 \cdot 0.26 = 0.25 + 0.98 + 0.78 = 2.01

Final Answer

μX=2.13 \boxed{\mu_X = 2.13} μY=2.01 \boxed{\mu_Y = 2.01}

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