Imagine a dataset with a negative skewness and a low kurtosis. How would this influence your data interpretation and statistical tests?
- It would not impact the interpretation or statistical tests.
- The data would be less likely to have outliers and the distribution would be wider.
- The data would be more likely to have outliers and the distribution would be narrow.
- The mean of the dataset would be greater than the median.
Negative skewness means that the tail of the distribution extends towards more negative values and most values are clustered around the right tail. Low kurtosis (or platykurtic) suggests that the data is flatter and more spread out than a normal distribution, indicating less likelihood of extreme outliers.
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