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- Histograms are particularly useful in determining the underlying probability distribution of a dataset, while box plots are more useful when comparing between multiple datasets. They are less detailed than histograms and take up less space.
citoolkit.com/articles/histograms-and-boxplots/Exploring Histograms and Box Plots: Similarities and Differences
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Histograms and box plots are very similar in their ability to visualize and describe numeric data. Although histograms are better in determining the underlying distribution of the data, box plots allow the comparison of multiple datasets as they are less detailed and take up less space.
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May 18, 2018 · A box plot shows only a simple summary of the distribution of results, so that it you can quickly view it and compare it with other data. Use a box plot in combination with another statistical graph method, like a histogram, for a more thorough, more detailed analysis of the data.
- Step 1: Compare The Medians of Box Plots
- Step 2: Compare The Interquartile Ranges and Whiskers of Box Plots
- Step 3: Look For Potential Outliers
Compare the respective medians of each box plot. If the median line of a box plot lies outside of the box of a comparison box plot, then there is likely to be a difference between the two groups. Source: https://blog.bioturing.com/2018/05/22/how-to-compare-box-plots/
Compare the interquartile ranges (that is, the box lengths) to examine how the data is dispersed between each sample. The longer the box, the more dispersed the data. The smaller, the less dispersed the data. Next, look at the overall spread as shown by the extreme values at the end of two whiskers. This shows the range of scores (another type of d...
When reviewing a box plot, an outlier is defined as a data point that is located outside the whiskers of the box plot.
Box plots truly shine when comparing data distributions across different groups. Their compact design offers a neat summary of data, making it a breeze to compare distributional properties of the groups through the positioning of box and whisker markings.
- Visualize the Distribution of Values in a Dataset. Suppose a basketball coach wants to visualize the distribution of points scored by players on his team so he creates the following box plot
- Compare Two or More Distributions. Suppose a sports analyst wants to compare the distribution of points scored by basketball players on three different teams so he creates the following box plots
- Identify Outliers. Suppose a basketball coach wants to know if any of his players are outliers in terms of points scored. He decides to create the following box plot to visualize the distribution of points scored by his players
1 day ago · The box plot helps identify the 25 th and 75 th percentiles better than the histogram, while the histogram helps you see the overall shape of your data better than the box plot. How do I create box plots?
Box plots are at their best when a comparison in distributions needs to be performed between groups. They are compact in their summarization of data, and it is easy to compare groups through the box and whisker markings’ positions. It is less easy to justify a box plot when you only have one group’s distribution to plot.
