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Statistics Examples
2 , 3 , 4 , 5 , 3 , 6 , 8 , 6 , 4 , 2
Step 1
The number of classes can be estimated using the rounded output of Sturges' rule, N=1+3.322log(n), where N is the number of classes and n is the number of items in the data set.
1+3.322log(6)=3.58501845
Step 2
Select 4 classes for this example.
4
Step 3
Find the data range by subtracting the minimum data value from the maximum data value. In this case, the data range is 8-2=6.
6
Step 4
Find the class width by dividing the data range by the desired number of groups. In this case, 64=1.5.
1.5
Step 5
Round 1.5 up to the nearest whole number. This will be the size of each group.
2
Step 6
Start with 2 and create 4 groups of size 2.
ClassClassBoundariesFrequency2-34-56-78-9
Step 7
Determine the class boundaries by subtracting 0.5 from the lower class limit and by adding 0.5 to the upper class limit.
ClassClassBoundariesFrequency2-31.5-3.54-53.5-5.56-75.5-7.58-97.5-9.5
Step 8
Draw a tally mark next to each class for each value that is contained within that class.
ClassClassBoundariesFrequency2-31.5-3.5||||4-53.5-5.5|||6-75.5-7.5||8-97.5-9.5|
Step 9
Count the tally marks to determine the frequency of each class.
ClassClassBoundariesFrequency2-31.5-3.544-53.5-5.536-75.5-7.528-97.5-9.51
Step 10
The relative frequency of a data class is the percentage of data elements in that class. The relative frequency can be calculated using the formula fi=fn, where f is the absolute frequency and n is the sum of all frequencies.
fi=fn
Step 11
n is the sum of all frequencies. In this case, n=4+3+2+1=10.
n=10
Step 12
The relative frequency can be calculated using the formula fi=fn.
ClassClassBoundariesFrequency(f)fi2-31.5-3.544104-53.5-5.533106-75.5-7.522108-97.5-9.51110
Step 13
Simplify the relative frequency column.
ClassClassBoundariesFrequency(f)fi2-31.5-3.540.44-53.5-5.530.36-75.5-7.520.28-97.5-9.510.1