To determine the best description for the data in Question 7, we need to analyze the data's distribution, skewness, and central tendency. Since the actual data from Question 7 is not provided, we cannot generate a Python code to solve this specific problem. However, if the data were provided, we would typically calculate the mean, median, and standard deviation, and then analyze the skewness and distribution shape.
For a general approach, here is how you might analyze a dataset in Python:
The question asks us to determine the best description of the data from Question 7. Since we do not have the data from Question 7, we need to analyze the given options and choose the most logical one based on typical data descriptions.
- Option A: "The data is spread out and skewed left."
- This means the data has a long tail on the left side and values are spread out.
- Option B: "Most of the data is far from the median and skewed right."
- This implies that the data has a long tail on the right side and most values are not close to the median.
- Option C: "The data is symmetrical, and the mean is close to the median."
- This suggests that the data is evenly distributed around the mean and median, indicating a normal distribution.
- Option D: "The data is spread out with 18 items being the most common number of items per load."
- This indicates that the data is spread out but has a mode of 18 items.
Without the actual data, we need to choose the most general and likely description. Typically, if data is symmetrical and the mean is close to the median, it suggests a normal distribution, which is a common scenario.