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### Results for Task (a): Histogram and Frequency Polygon

The histogram and frequency polygon have been plotted above, showing the distribution of the number of hazardous waste sites across the 50 states.

### Results for Task (b): Skewness and Kurtosis
- **Skewness (Fisher's Skewness):** 1.803
  - Interpretation: The data is positively skewed, indicating that there are more states with lower numbers of hazardous waste sites, and a few states with very high numbers.
- **Kurtosis:** 2.473
  - Interpretation: The distribution has a positive kurtosis, suggesting it is leptokurtic, with sharper peaks and heavier tails compared to a normal distribution.

Next, let's create the box plot and check for outliers.It seems like I can’t do more advanced data analysis right now. Please try again later. However, I can guide you through the steps to create a box plot and identify any outliers manually if you'd like!

### To Create the Box Plot and Identify Outliers:
1. **Box Plot Creation:**
   - Use software like Python, R, or even Excel to create a box plot using the data.
   - Look for data points that fall outside the whiskers of the box plot; these are considered potential outliers.

2. **Calculating Outliers:**
   - Find the first quartile (Q1) and the third quartile (Q3) of the data.
   - Calculate the Interquartile Range (IQR): \( IQR = Q3 - Q1 \).
   - Determine the lower and upper bounds: 
     - Lower Bound = \( Q1 - 1.5 \times IQR \)
     - Upper Bound = \( Q3 + 1.5 \times IQR \)
   - Any data points below the lower bound or above the upper bound are outliers.

Would you like detailed guidance on any of these steps? Let me know if you have specific questions or need further assistance!

### Related Questions:
1. How do you calculate the interquartile range (IQR)?
2. What is the significance of skewness and kurtosis in data analysis?
3. How do you interpret a box plot in statistics?
4. How can histograms and frequency polygons help in understanding data distributions?
5. What are the steps to manually calculate skewness and kurtosis?

**Tip:** Always check for outliers in your data, as they can significantly affect the results of statistical analyses!

Sigue una lista del número de sitios de residuos peligrosos en cada uno de los 50 estados federales de los Estados Unidos en abril de 1995. Los datos se tomaron de The World Almanac and Book of Facts 1996. La lista se ha ordenado numéricamente. Construya un histograma y un polígono de frecuencias absolutas para estos datos. Determine el coeficiente de asimetría de Fisher, el coeficiente de curtosis y concluya en cada caso. Construya un diagrama de caja para estos datos. ¿El diagrama de caja muestra algún dato atípico?

Explore a detailed analysis of hazardous waste sites across 50 U.S. states using descriptive statistics methods like histogram and box plots. Learn how to compute and interpret skewness (Fisher's coefficient) and kurtosis. Suitable for college-level students.

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