Sometimes the reason for using unequal class intervals in frequency distributions is because each side of the parameter is particularly small. The use of unequal class intervals is all dependent on the data collected and how it is being investigated. The data is then used to create a histogram to give a graphical representation of the data.
Histograms are similar in appearance to bar graphs, however they are not the same. This is because in a bar graph the width or each bar remains the same and each bar is entirely separate from another.
Whereas with a histogram, the width represents the class intervals, and the bars are all joined or adjacent to each other
Usually, the class intervals used within a frequency distribution are equal. For example, they may increase by five each time throughout each interval. This is more common with frequency distributions simply because there are enough intervals to accommodate this.
However - in the event of the entire collection of class intervals being very small, it may not be possible to have completely even intervals. In which case, statisticians are required to create unequal intervals to accommodate the spread of the data.
Regardless of which type of class interval you are using, so long as you have done the frequency distribution correctly then your data will always be valid. Even if there is a small range of data it is still possible for you to compile this data into a histogram or other appropriate graphical representation of your choosing.
- Characteristics of histograms
Histograms are similar in appearance to bar graphs, however they are not the same. This is because in a bar graph the width or each bar remains the same and each bar is entirely separate from another.
Whereas with a histogram, the width represents the class intervals, and the bars are all joined or adjacent to each other
Usually, the class intervals used within a frequency distribution are equal. For example, they may increase by five each time throughout each interval. This is more common with frequency distributions simply because there are enough intervals to accommodate this.
However - in the event of the entire collection of class intervals being very small, it may not be possible to have completely even intervals. In which case, statisticians are required to create unequal intervals to accommodate the spread of the data.
- Why frequency distributions need to be calculated carefully
Regardless of which type of class interval you are using, so long as you have done the frequency distribution correctly then your data will always be valid. Even if there is a small range of data it is still possible for you to compile this data into a histogram or other appropriate graphical representation of your choosing.
