Class interval
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Class Interval

 Sturgis's Rule: Set the number of class intervals as close as possible to [math]1 + log_{2}n\,[/math], where [math]log_{2}n\,[/math] is the base [math]2[/math] logarithm of the number of observations, n. The formula can also be written as [math]1 + 3.3\,log_{10}n\,[/math] where [math]log_{10}n\,[/math] is the base [math]10[/math] logarithm of the number of observations. According to Sturgis' rule, [math]1000[/math] observations would be graphed with [math]11[/math] class intervals since [math]10[/math] is the closest integer to [math]log_{2}1000\,[/math].
 Rice Rule: Set the number of class intervals to twice the cube root of the number of observations. In the case of [math]1000[/math] observations, the Rice rule yields [math]20[/math] class intervals (compared to the [math]11[/math] recommended by Sturgis' rule).
 Experiment with different choices of width, choosing an interval width according to how well it communicates the shape of the distribution when displayed as a histogram.
Examples
Pulse rates, in beats per minute, were calculated for [math]192[/math] students enrolled in a statistics course at the University of Adelaide.^{[2]} The pulse rates in the dataset range from [math]35[/math] to [math]104[/math] beats per minute, [math]70[/math] possible values. An ungrouped frequency distribution listing the counts for each of the [math]70[/math] possible values will be large and cumbersome to interpret effectively. Interpretation is simplified by grouping the data into class intervals.
Use the number of observations, in this example [math]n=192\,[/math], to determine the number of class intervals to use in a grouped frequency distribution:
 Sturgis's rule, [math]1 + 3.3\,log_{10}192=8.6\,[/math], suggests [math]8[/math] or [math]9[/math] class intervals.
 The Rice rule, [math]2 \times \sqrt[3]{192}=11.54[/math], suggests [math]11[/math] or [math]12[/math] class intervals.
There is no right answer for the number of class intervals. For this example we will group the data into [math]10[/math] classes, splitting the difference between the two methods.
The following frequency table provides the count and percent for the data values grouped into [math]10[/math] class intervals.
Pulse Rate*  Count  Percent 

(3441]  2  1.0% 
(4148]  2  1.0% 
(4855]  4  2.1% 
(5562]  19  9.9% 
(6269]  40  20.8% 
(6976]  53  27.6% 
(7683]  30  15.6% 
(8390]  27  14.1% 
(9097]  10  5.2% 
(97104]  5  2.6% 
Total  192  100.0% 
 The limits of each class are indicated by the parenthesis, which means
"not including", and the square bracket, which means "including".
Notes
 ↑ "Histograms" in Chapter: 2. Graphing Distributions. Online Statistics: An Interactive Multimedia Course of Study. Retrieved on 20090212.
 ↑ See the dataset, survey, available in the MASS package in R, an open source statistical computing software application.