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In most situations, we usually consider a very large amount of data(like population census) for a purposeful study. In such cases, we may find it difficult to write the data in ungrouped data.
 
Hence, to simplify our work, we need to convert the given ungrouped data into grouped data.
 
Let us convert the given height(in cm) of the students in the classroom into grouped frequency data.
 
100, 165, 189, 155, 140, 196, 165, 135, 135, 100, 100, 100, 155, 165, 196, 189, 177, 163, 177, 130.
 
Consider the frequency distribution table.
 
Height (in cm)100 - 120120 - 140140 - 160160 - 180180 - 200
Students43364
 
The above frequency table shows that the data are grouped in class intervals.
 
Consider the interval 140 - 160. There are 3 students in the heights between 140 - 160 metres. In grouped frequency, individual observations are not available. Thus, we need to determine the value that indicates the particular interval. This value is called a midpoint or class mark. The midpoint can be determined using the formula:
 
Midpoint = \frac{UCL + LCL}{2}
 
Where UCL is the upper class limit and LCL is the lower class limit.
Example:
Consider the interval 140 - 160. Let us find the midpoint of this interval.
 
Here, UCL = 140 and LCL = 160
 
Midpoint of 140 - 160 is \frac{140 + 160}{2} = \frac{300}{2} = 150
 
Therefore, the midpoint of the interval 140 - 160 is 150.
The mean of a grouped frequency distribution can be determined using any one of the following methods.
  • Direct method
  • Assumed mean method
  • Step deviation method