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) $\mu_X$ and $\mu_Y$, 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 $\mu_X$, we sum over all possible values of $X$ weighted by their marginal probabilities. Similarly, for $\mu_Y$, we sum over all possible values of $Y$ weighted by their marginal probabilities.

Step 1: Calculate Marginal Probabilities for \(X\)

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

Step 2: Calculate Marginal Probabilities for \(Y\)

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

Step 3: Calculate Expected Value \(\mu_X\)

The expected value \(\mu_X\) is calculated by summing the product of each value of \(X\) and its marginal probability: \[ \mu_X = 1 \cdot 0.19 + 2 \cdot 0.49 + 3 \cdot 0.32 = 0.19 + 0.98 + 0.96 = 2.13 \]

Step 4: Calculate Expected Value \(\mu_Y\)

The expected value \(\mu_Y\) is calculated by summing the product of each value of \(Y\) and its marginal probability: \[ \mu_Y = 1 \cdot 0.25 + 2 \cdot 0.49 + 3 \cdot 0.26 = 0.25 + 0.98 + 0.78 = 2.01 \]

Final Answer

\[ \boxed{\mu_X = 2.13} \] \[ \boxed{\mu_Y = 2.01} \]

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