• Compare data sets by describing their shapes, centers, spreads, and outliers

Let’s analyze the salary data set in the statistical tool and create side-by-side dotplots or histograms.

By displaying the data set in side-by-side dotplots or histograms, we can describe and compare features of the distribution of the quantitative variable. The features used to describe the distribution of a quantitative variable are the shape, center, spread, and presence of outliers.

How do we decide when to use a dotplot and when to use a histogram? There are no rules here. Each type of graph can highlight different aspects of the data.

• Here are some observations about dotplots:
  • Individual variable values are visible, particularly when the data set is small.
  • Descriptions of shape, center, and spread are not affected by how the dotplot is constructed.
  • We can accurately calculate the overall range (largest value – smallest value).
• Here are some observations about histograms:
  • Individual variable values are not visible.
  • Grouping individuals into bins of equal-sized intervals is particularly useful when analyzing large data sets.
  • We can easily use percentages, also called relative frequencies, to describe the distribution.
  • Descriptions of shape, center, and spread are affected by how the bins are defined.

Create the dotplots or histograms for the data set “Recent Grads – Salary” using the Describing and Exploring Quantitative Data tool to answer additional questions.

Steps to create side-by-side dotplots

STEP 1: Click the “Several Groups” tab at the top of the page.

STEP 2: Select data set “Recent Grads – Salary.”

STEP 3: Select “Histogram” or “Dotplot” and adjust the “binwidth” or “dot size” appropriately.

Note: The dotplots will display their horizontal axes in scientific notation. For example: “2e+04” = 20,000.

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