Which type of plot should one avoid when discussing gaps and clusters in a data set?

Which type of plot should one avoid when discussing gaps and clusters in a data set?

• A. Scatterplot
• B. Boxplot
• C. Bar chart
• D. Line graph

Answer: (B)

In discussing gaps and clusters within a data set, a boxplot is not the most effective choice because it is primarily designed to summarize the distribution and central tendency of quantitative data. It provides insights into measures like the median, quartiles, and potential outliers by showing the interquartile range and overall spread of the data. While a boxplot can indicate variability and outliers, it does not convey information about the detailed structure of the data distribution with respect to gaps and clusters. On the other hand, scatterplots are particularly useful for visualizing relationships between two quantitative variables and can effectively show gaps and clusters. Bar charts can represent categorical data, where gaps and clusters may be represented by the height of the bars illustrating different categories. Line graphs are useful for showing trends over time and can also highlight clusters in data when examining a continuous variable. Therefore, when the focus is on identifying gaps and clusters, the boxplot falls short compared to these other visualizations.

In discussing gaps and clusters within a data set, a boxplot is not the most effective choice because it is primarily designed to summarize the distribution and central tendency of quantitative data. It provides insights into measures like the median, quartiles, and potential outliers by showing the interquartile range and overall spread of the data. While a boxplot can indicate variability and outliers, it does not convey information about the detailed structure of the data distribution with respect to gaps and clusters.

On the other hand, scatterplots are particularly useful for visualizing relationships between two quantitative variables and can effectively show gaps and clusters. Bar charts can represent categorical data, where gaps and clusters may be represented by the height of the bars illustrating different categories. Line graphs are useful for showing trends over time and can also highlight clusters in data when examining a continuous variable. Therefore, when the focus is on identifying gaps and clusters, the boxplot falls short compared to these other visualizations.