\begin{tabular}{l|l|} The distribution is & (Choose one) \\ & \( \begin{array}{l}\text { somewhat negatively skewed } \\ \text { approximately normal } \\ \text { somewhat positively skewed }\end{array} \) \\ \hline\end{tabular}

1. First, we recall that a probability distribution can be classified by its skewness. If most of its values cluster to one side with a tail on the other, it is said to be skewed. - If the tail extends further to the right, the distribution is positively skewed. - If the tail extends further to the left, the distribution is negatively skewed. 2. In contrast, if the data are balanced about a central point with a bell‐shaped curve, then the distribution is approximately normal (symmetric). 3. Without additional specific details (such as a histogram, descriptive statistics, or values like the mean, median, and mode), we typically look at the context or description provided in the problem. In many textbook problems when a distribution is described without noting any obvious asymmetry, it is common to assume that the distribution is approximately normal. 4. Thus, based on the usual interpretation when no additional skew details are given, we choose \[ \text{approximately normal}. \]