A histogram represents the distribution of quantitative data by grouping values into contiguous, equal-width intervals, with touching bars whose heights show frequency or relative frequency; the intervals, boundaries, scale, and bar heights must faithfully preserve how observations are allocated. Interpretation includes describing modality, clusters, gaps, skewness, typical values, variability, and possible outliers, while distinguishing histograms from bar graphs for categorical data; unequal-width bins and frequency-density scaling are not included.
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A histogram shows how quantitative data are distributed. To make one:
The following data show the number of minutes 20 students spent exercising in one week:
Use intervals of width :
Writing intervals with “less than” avoids ambiguity. For example, a value of belongs in to less than , not in to less than .
| Exercise time (minutes) | Frequency |
|---|---|
| to less than | |
| to less than | |
| to less than | |
| to less than | |
| to less than | |
| to less than |
Check that the frequencies add to the total number of observations:
Put the intervals on the horizontal axis and frequency on the vertical axis. Draw rectangles with these heights:
The bars should touch each other. The empty interval from to less than appears as a gap, and the bar from to less than has height .
From the histogram, we can say:
A histogram is used for quantitative data, such as time, height, or test score. A bar graph is used for categorical data, such as favorite sports or eye color. Histogram bars touch; bar graph bars usually have spaces between them.
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