How does the Z-score method perform when the data is not normally distributed?
- It performs better
- It performs the same
- It performs worse
- Its performance is independent of the data distribution
Z-score method assumes a Gaussian distribution and can perform poorly when data is not normally distributed, possibly leading to an over or under identification of outliers.
Loading...
Related Quiz
- You have a dataset in which the 'income' feature has some missing values. You decided to use mode imputation. Why could this lead to misleading results?
- What does the term "Multicollinearity" refer to in the context of Exploratory Data Analysis?
- What are some of the major limitations of Matplotlib that Plotly and Seaborn help to overcome?
- How many variables can a heatmap typically visualize at once?
- What is the name of the statistical measure that shows the degree of the relationship between two variables?