Intro to stats symmetry vs skew and missing data values questions

1) You are right. A and B are true.

If the distribution is symmetric, then the mean is equal to the median, and the distribution has zero skewness. Skewness is defined as $ \frac{(\mu -\nu )}{\sigma }$ where $\mu$ is the mean, $\nu$ is the median, and $\sigma$ is the standard deviation, the skewness is defined in terms of this relationship: positive/right nonparametric skew means the mean is greater than (to the right of) the median, while negative/left nonparametric skew means the mean is less than (to the left of) the median. 

There are more sophisticated ways to measure skewness and symmetry. For example Pearson's moment coefficient of skewness. See the following Wiki page for more info: 

https://en.wikipedia.org/wiki/Skewness#Relationship_of_mean_and_median

2- I think ABCD are all correct. If data is coded as M or N/A, this could sometimes cause problems in certain software as the program may expect a numeric data for that cell and not an alphabetical text. Part E is clearly not true as there are many methods to estimate or replace missing data. For example see: 

https://www.mastersindatascience.org/learning/how-to-deal-with-missing-data/