II character? (A) Skewed to the right (B) Skewed to the left (C) Normal (D) Approximately normal (E) Symmetric, but not approximately normal 16

To determine the skewness of a distribution, we need to analyze the characteristics of the data provided.

Analysis of Options:

1. Skewed to the Right (A): This means that the tail on the right side of the distribution is longer or fatter than the left side. It indicates that there are a number of high values in the dataset.

2. Skewed to the Left (B): Opposite to right skewness, this indicates that the tail on the left side is longer or fatter, and there are a number of low values in the dataset.

3. Normal (C): A perfectly normal distribution is symmetric about the mean, with no skewness.

4. Approximately Normal (D): This suggests that while the distribution is not perfectly normal, it closely resembles a normal distribution in shape.

5. Symmetric, but not Approximately Normal (E): This indicates that the distribution is symmetric, but lacks the properties of a normal distribution (e.g., it may have different heights or a different shape).

Conclusion

Without additional context or data, it is not possible to definitively select one of these options. Each choice describes a different type of distribution.

If you have specific data or graphical representation, please provide it for a more accurate assessment. In the absence of that information, it would be advisable to look at the characteristics of the data to decide.