Explanation

To calculate the unbiased sample variance, we use the formula:

$s^2 = \frac{\sum_{i=1}^{n}(x_i - \bar{x})^2}{n-1}$

Where:

• n = sample size = 5
• x_i = individual returns
• \bar{x} = sample mean

Step 1: Calculate the mean $\bar{x} = \frac{21 + 17 + 11 + 18 + 15}{5} = \frac{82}{5} = 16.4$

Step 2: Calculate squared deviations from mean $(21 - 16.4)^2 = (4.6)^2 = 21.16$ $(17 - 16.4)^2 = (0.6)^2 = 0.36$ $(11 - 16.4)^2 = (-5.4)^2 = 29.16$ $(18 - 16.4)^2 = (1.6)^2 = 2.56$ $(15 - 16.4)^2 = (-1.4)^2 = 1.96$

Step 3: Sum of squared deviations $\sum(x_i - \bar{x})^2 = 21.16 + 0.36 + 29.16 + 2.56 + 1.96 = 55.2$

Step 4: Calculate unbiased sample variance $s^2 = \frac{55.2}{5-1} = \frac{55.2}{4} = 13.8$

Step 5: Convert to decimal form Since the returns are given in percentages, we need to convert the variance to decimal form: $s^2 = \frac{13.8}{100^2} = \frac{13.8}{10000} = 0.00138$

Therefore, the correct unbiased sample variance is 0.00138, which corresponds to option B.