Emphasize the cumulative nature of a histogram.

Link the relevant Wikipedia entry.

content/docs/concepts/metric_types.md

@@ -55,13 +55,15 @@ during a scrape:
   * the **total sum** of all observed values, exposed as `<basename>_sum`
   * the **count** of events that have been observed, exposed as `<basename>_count` (identical to `<basename>_bucket{le="+Inf"}` above)
 
-Use the [`histogram_quantile()`
-function](/docs/querying/functions/#histogram_quantile) to calculate
-quantiles from histograms or even aggregations of histograms. A
-histogram is also suitable to calculate an [Apdex
-score](http://en.wikipedia.org/wiki/Apdex). See [histograms and
-summaries](/docs/practices/histograms) for details of histogram usage
-and differences to [summaries](#summary).
+Use the
+[`histogram_quantile()` function](/docs/querying/functions/#histogram_quantile)
+to calculate quantiles from histograms or even aggregations of histograms. A
+histogram is also suitable to calculate an
+[Apdex score](http://en.wikipedia.org/wiki/Apdex). When operating on buckets,
+remember that the histogram is
+[cumulative](https://en.wikipedia.org/wiki/Histogram#Cumulative_histogram). See
+[histograms and summaries](/docs/practices/histograms) for details of histogram
+usage and differences to [summaries](#summary).
 
 Client library usage documentation for histograms:
 

content/docs/practices/histograms.md

@@ -80,8 +80,10 @@ following expression yields the Apdex score for each job over the last
     ) / 2 / sum(rate(http_request_duration_seconds_count[5m])) by (job)
 
 Note that we divide the sum of both buckets. The reason is that the histogram
-buckets are cumulative. The `le="0.3"` bucket is also contained in the `le="1.2"`
-bucket; dividing it by 2 corrects for that.
+buckets are
+[cumulative](https://en.wikipedia.org/wiki/Histogram#Cumulative_histogram). The
+`le="0.3"` bucket is also contained in the `le="1.2"` bucket; dividing it by 2
+corrects for that.
 
 ## Quantiles