Frequency Distribution is a method of organizing data that shows how often each value or group of values occurs in a dataset.
Example 1: Suppose we have a series with a mean of 20 and a variance of 100. Find out the Coefficient of Variation.Â
Solution:Â
We know the formula for Coefficient of Variation,Â
\frac{\sigma}{\bar{x}} \times 100 Given meanÂ
\bar{x} Â = 20 and varianceÂ\sigma^2 Â = 100.ÂWe know ,
Standard Deviation
\sigma=\sqrt{varience}=\sqrt{100} Standard Deviation
\sigma=10 Substituting the values in the formula,
\frac{\sigma}{\bar{x}} \times 100 \\ = \frac{10}{20} \times 100 \\ = \frac{10}{20} \times 100 \\ = 50
Example 2: Given two series with Coefficients of Variation of 70 and 80. The means are 20 and 30. Find the values of the standard deviation for both series.
Solution:Â
In this question we need to apply the formula for CV and substitute the given values.Â
Standard Deviation of first series.Â
C.V = \frac{\sigma}{\bar{x}} \times 100 \\ 70 = \frac{\sigma}{20} \times 100 \\ 1400 = \sigma \times 100 \\ \sigma=14 Thus, the standard deviation of first series = 14
Standard Deviation of second series.Â
C.V = \frac{\sigma}{\bar{x}} \times 100 \\ 80 = \frac{\sigma}{30} \times 100 \\ 2400 = \sigma \times 100 \\ \sigma=24 Thus, the standard deviation of first series = 24
Example 3: Draw the frequency distribution table for the following data:Â 2, 3, 1, 4, 2, 2, 3, 1, 4, 4, 4, 2, 2, 2
Solution:Â
Since there are only very few distinct values in the series, we will plot the ungrouped frequency distribution.Â
Value  Frequency 1
2
2
6
3
2
4
4
TotalÂ
14
Example 4: The table below gives the values of temperature recorded in Hyderabad for 25 days in summer. Represent the data in the form of a less-than-type cumulative frequency distribution:Â
| 37 | 34 | 36 | 27 | 22 |
| 25 | 25 | 24 | 26 | 28 |
| 30 | 31 | 29 | 28 | 30 |
| 32 | 31 | 28 | 27 | 30 |
| 30 | 32 | 35 | 34 | 29 |
Solution:Â
Since there are so many distinct values here, we will use grouped frequency distribution. Let's say the intervals are 20-25, 25-30, 30-35. Frequency distribution table can be made by counting the number of values lying in these intervals.Â
Temperature Number of Days 20-25
2
25-30
10
30-35
13
This is the grouped frequency distribution table. It can be converted into cumulative frequency distribution by adding the previous values.Â
Temperature Number of Days Less than 25
2
Less than 30
12
Less than 35
25
Example 5: Make a Frequency Distribution Table for the data:
{45, 22, 37, 18, 56, 33, 42, 29, 51, 27, 39, 14, 61, 19, 44, 25, 58, 36, 48, 30, 53, 41, 28, 35, 47, 21, 32, 49, 16, 52, 26, 38, 57, 31, 59, 20, 43, 24, 55, 17, 50, 23, 34, 60, 46, 13, 40, 54, 15, 62}
Solution:
To create the frequency distribution table for given data, let's arrange the data in ascending order as follows:
{13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62}
Now, we can count the observations for intervals: 10-20, 20-30, 30-40, 40-50, 50-60 and 60-70.
Interval Frequency 10 - 20 7 20 - 30 10 30 - 40 10 40 - 50 10 50 - 60 10 60 - 70 3