To find the value of skewness, we can compute it using the sample standard deviation and the third moment:

1. Calculate the sample variance ($s^2$): $s^2 = \frac{1}{n - 1} \sum_{i=1}^{n} (x_i - \hat{\mu})^2$ $s^2 = \frac{774,759.90}{200 - 1} = \frac{774,759.90}{199} \approx 3,893.2658`$2. Calculate the sample standard deviation ($s$): $s = \sqrt{3,893.2658} \approx 62.396$3`. Calculate the skewness:$Skewness = \frac{\frac{1}{n} \sum_{i=1}^{n} (x_i - \hat{\mu})^3}{s^3}$$Skewness = \frac{-13,476.784 / 200}{(62.396)^3} = \frac{-67.38392}{242,927.98} \approx -0.00027738$

Rounding to 7 decimal places, the skewness is approximately -0.0002774. Therefore, Option A is correct.