What is the impact of positive skewness on data interpretation?
- It suggests that data is evenly distributed.
- It suggests that most values are clustered around the left tail.
- It suggests that most values are clustered around the right tail.
- It suggests the presence of numerous outliers in the left tail.
Positive skewness indicates that most of the data values are clustered around the left tail of the distribution, with the tail extending towards more positive values. This could potentially lead to the mean being larger than the median.
Loading...
Related Quiz
- How do outliers affect the performance of machine learning models?
- What is the effect of redundant features on a machine learning model?
- How does the Variance Inflation Factor (VIF) quantify the severity of Multicollinearity in a regression analysis?
- How do outliers affect the standard deviation of a dataset?
- Can multiple imputation be applied when data are missing completely at random (MCAR)?