Sample Histogram

Construct a histogram of the measurements in the table below.

 Title Price Title Price Moulin Rouge \$23.85 Back in U.S. Live \$20.05 \$15.07 \$17.87 \$24.89 \$17.49 \$19.40 \$19.99 Grease \$21.15 Wizard of Oz \$20.52 \$15.74 \$15.88 \$19.74 \$19.98 \$22.10 \$20.29 \$17.22 \$17.99 \$20.74 \$18.34 Sound of Music \$18.00 \$21.23 \$23.99 \$18.99

The sample histogram below illustrates how the frequency of the data is related to one variable, in this case: price.  Later more elaborate graphs will look for patterns comparing two or more variables.

• Every histogram should have a title.
• Each axis should be labelled with (1) the property, (2) the units in (parentheses), and be numbered with (3) a scale.
• The scale difference from one division to the next must be uniform.  The price scale increases by \$1 per division and the frequency scale increases by 1 price per division, but other uniform, appropriate quantities would be acceptable.  For example, the bin size could have been increased by 10¢, \$0.50, or \$5 per division, but not on the same graph.
• The numbers match the bin boundary lines, NOT the bin space.  That way values in between (such as \$19.74) belong in a bin (between the \$19 and \$20 boundaries).
• The number of stacked markers shows the number of measurements that fit in that bin.  For example, there were four DVDs that had prices between \$19 and \$20.

Again, the purpose of a graph is to make apparent any patterns in the numbers.  This graph shows that popular DVDs do not all sell for the same price.  They range in price from \$15 to \$25 with the most common price, the mode, being about \$20.