project: Skewness and Kurtosis - Questions

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Questions

  1. Define skewness. What does it mean if a dataset is positively skewed versus negatively skewed? Provide an example of each.

  2. How is skewness calculated, and what do the resulting values indicate about the distribution of a dataset?

  3. Explain kurtosis and its significance. How does high kurtosis differ from low kurtosis in terms of the distribution’s peak?

  4. How does skewness affect statistical analyses and decision-making? Give an example of how skewness might impact financial data interpretation.

  5. Provide an example of a real-life dataset that is likely to be skewed. Explain how skewness affects the analysis and interpretation of this data.


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