Sturges' rule is a way of calculating the number of bins (e.g. categories or classes) of a set of data. It is assumed that the data come from a normally distributed population.
Sturges' rule states that the number of bins should be the ceiling function of (1+log(2)n) (log base 2 of n, where the ceiling function returns the next higher integer.)
Here we have 1+log(2)100 is approximately 1+6.64385619=7.64385619 so the number of bins should be...
Sturges' rule is a way of calculating the number of bins (e.g. categories or classes) of a set of data. It is assumed that the data come from a normally distributed population.
Sturges' rule states that the number of bins should be the ceiling function of (1+log(2)n) (log base 2 of n, where the ceiling function returns the next higher integer.)
Here we have 1+log(2)100 is approximately 1+6.64385619=7.64385619 so the number of bins should be 8.
We can find the class width by (111200-74800)/8=4550, so we use 4551 as the class width.
74799.5 - 79350.5
79350.5 - 83901.5
83901.5 - 88452.5
88452.5 - 93003.5
93003.5 - 97554.5
97554.5 - 102105.5
102105.5 - 106656.5
106656.5 - 111207.5
**If the data is in hundreds, the boundaries would be in 50's **
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