Questions: Coffee with Meals A researcher wishes to determine the number of cups of coffee a customer drinks with an evening meal restaurant. X 0 1 2 3 4 P(X) 0.21 0.30 0.46 0.01 0.02 Find the mean. Round the answer to two decimal places as needed. Mean: μ=1.33 Find the variance. Round the answer to two decimal places as needed. Variance: σ^2=

Coffee with Meals A researcher wishes to determine the number of cups of coffee a customer drinks with an evening meal restaurant.

X 0 1 2 3 4
P(X) 0.21 0.30 0.46 0.01 0.02

Find the mean. Round the answer to two decimal places as needed.
Mean: μ=1.33

Find the variance. Round the answer to two decimal places as needed.
Variance: σ^2=
Transcript text: Coffee with Meals A researcher wishes to determine the number of cups of coffee a customer drinks with an evening meal restaurant. \begin{tabular}{c|ccccc} $\boldsymbol{X}$ & 0 & 1 & 2 & 3 & 4 \\ \hline $\boldsymbol{P}(\boldsymbol{X})$ & 0.21 & 0.30 & 0.46 & 0.01 & 0.02 \end{tabular} Find the mean. Round the answer to two decimal places as needed. Mean: $\mu=1.33$ Find the variance. Round the answer to two decimal places as needed. Variance: $\sigma^{2}=$ $\square$
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Solution

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Solution Steps

Step 1: Calculate the Mean

The mean \( \mu \) of the distribution is calculated using the formula:

\[ \mu = \sum_{i=0}^{n} x_i \cdot P(x_i) \]

Substituting the values:

\[ \mu = 0 \times 0.21 + 1 \times 0.30 + 2 \times 0.46 + 3 \times 0.01 + 4 \times 0.02 = 1.33 \]

Step 2: Calculate the Variance

The variance \( \sigma^2 \) is calculated using the formula:

\[ \sigma^2 = \sum_{i=0}^{n} (x_i - \mu)^2 \cdot P(x_i) \]

Substituting the values:

\[ \sigma^2 = (0 - 1.33)^2 \times 0.21 + (1 - 1.33)^2 \times 0.3 + (2 - 1.33)^2 \times 0.46 + (3 - 1.33)^2 \times 0.01 + (4 - 1.33)^2 \times 0.02 = 0.78 \]

Step 3: Calculate the Standard Deviation

The standard deviation \( \sigma \) is the square root of the variance:

\[ \sigma = \sqrt{\sigma^2} = \sqrt{0.78} \approx 0.88 \]

Final Answer

The results are as follows:

  • Mean: \( \mu = 1.33 \)
  • Variance: \( \sigma^2 = 0.78 \)
  • Standard Deviation: \( \sigma \approx 0.88 \)

Thus, the final boxed answers are:

\[ \boxed{\mu = 1.33} \] \[ \boxed{\sigma^2 = 0.78} \] \[ \boxed{\sigma \approx 0.88} \]

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