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
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}
Solution
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:
\[
\mu_Y = 1 \cdot 0.25 + 2 \cdot 0.49 + 3 \cdot 0.26 = 0.25 + 0.98 + 0.78 = 2.01
\]