Consider you are dealing with a dataset with zero skewness but high kurtosis. How would this shape the data distribution and affect your analysis?
- The data distribution would be negatively skewed with a wider spread.
- The data distribution would be perfectly symmetrical with a narrower spread and potential outliers.
- The data distribution would be perfectly symmetrical with a wider spread.
- The data distribution would be positively skewed with a narrower spread.
Zero skewness means the distribution is symmetrical, and high kurtosis means the distribution is leptokurtic with a sharp peak and fatter tails. Therefore, the data distribution will be symmetrical but with a potential for outliers. This may affect the results of statistical tests or models that assume normality, as extreme values could have a disproportionate effect on the results.
Loading...
Related Quiz
- Imagine you're dealing with a classification model. The dataset has a significant amount of missing data that was replaced with the mean. How could this decision have impacted the model's performance?
- What is the potential impact of outliers on the analysis of a dataset?
- In a positively skewed distribution, which is greater: mean or median?
- During the '______' phase of the EDA process, you might use visualization techniques to understand the patterns in your data.
- Multicollinearity can make the regression coefficients _________.