The question in the image asks which graph most likely corresponds to a normal distribution. Here's how to analyze it:

Analysis of Boxplots

1. Normal distribution implies symmetry around the mean, minimal outliers, and equal spread between the quartiles.
2. Boxplot Features to Consider:
   • The box (interquartile range, IQR) should be centered between the whiskers.
   • There should be minimal or no outliers.
   • The whiskers should have a roughly symmetric length.

Observations:

• Graph A: Symmetric, few outliers, equal whiskers — a possible candidate for normality.
• Graph B: Many outliers, right-skewed. This is not normal.
• Graph C: Few outliers, symmetric whiskers, centered IQR — the best match for normal distribution.
• Graph D: Many outliers and uneven whiskers — not normal.

Conclusion:

Graph C best fits the criteria for a normal distribution.

Would you like a detailed explanation of why the others were ruled out, or help understanding boxplot analysis further?

Related Questions:

1. What are the common characteristics of a normal distribution in statistical graphs?
2. How can skewness in a dataset be identified using a boxplot?
3. What does the presence of outliers suggest about the underlying distribution?
4. How do boxplots compare to histograms for assessing normality?
5. Can transformations be applied to make a dataset with outliers more normal?

Tip:

When analyzing boxplots, always check symmetry and the spread of data. Fewer outliers often suggest a distribution closer to normality.