Final answer:
If the errors are positively skewed, applying a log transformation can help reduce skewness. It is important to consider the shape of the data and choose the most appropriate measure of center.
Step-by-step explanation:
If you suspect that the errors in your data are positively skewed, a possible solution is to apply a **log transformation**. This transformation can help to reduce the skewness by compressing the larger values and stretching the smaller values.
Ignoring the skewness (option C) may lead to biased or inaccurate results, so it's not recommended. Excluding the skewed data (option D) should only be done after careful consideration, as it may result in loss of important information.
By examining the shape of the data, option A (applying a log transformation) gives a more appropriate result for positively skewed data. For positively skewed data, the **median** is often a more appropriate measure of center than the mean, as the mean can be influenced by extreme values.