Explain how the shape of a distribution determines the appropriate measure of center. (1 point) skewed data means that the mean is the best measure of center. Symmetrical data means that the mean is the best measure of center. The shape does not matter when determining the appropriate measure of center. More information is needed to determine how the data of distribution determines the appropriate measure of center.

When dealing with skewed data, the mean can be misleading because it is pulled in the direction of the skew. In such cases, the median becomes the preferred measure of center as it provides a more accurate reflection of the dataset's "center" without being influenced by extreme values. Remember, the mean might show an inflated or deflated average that doesn’t truly represent typical values! On the flip side, when data is symmetrical, both the mean and median will give you practically the same result, making the mean a suitable measure of center. This is because symmetrical distributions, like the classic bell curve, don’t have outliers to skew the average. So, if you see a symmetrical shape, feel free to take the mean and crown it as the champion of central tendencies!