The Frequency Distribution

Data collection is an important part of the analysis, and when it comes to statistics, frequency distribution plays an important part. The next step after data collection is the organization of data into a meaningful form so that it becomes easier for people to understand the information and process it accordingly. For such a process, the frequency distribution is one of the most common methods to represent data in an organized manner. It is a very convenient method for researchers and people as it helps to analyze the full data quite easily. 

What is frequency distribution?

In simpler terms, we can define frequency distribution as a representation of data either in graphical format or in tabular format. Such format represents the data or observation over a given interval. The duration of the interval depends on the data that you are analyzing and on the goal of the researcher or the analyst that he/she wishes to analyze. In deciding the intervals, one should keep in mind that they should be exclusive and exhaustive. We use such distributions generally in a statistical context.

A frequency distribution shows you two possibilities one. It can show you an actual number that falls under the range. Second, they show the percentage of such observation, and in the case of percentage, we call such observation a relative frequency distribution. We could use a frequency distribution table for both numerical and categorical variables. Though continuous variables one should use along with class intervals only.

Class Interval

If you are dealing with a larger number of values and data, then it is easier to represent the data with the help of class intervals. It is quite easy for you to handle the data when you group them into one particular class. Variables that are in the continuation are more likely to present in class intervals. On the other hand, when we talk about discrete variables, you can either put them into class variables or not. It does not make much difference.

The frequency of any class interval is the number of observations that happens in one predefined interval. For instance, if 20 people aged 4 to 10 appear on our database, the frequency for the 4-10 interval will be 20. The endpoints of such intervals are the values that are highest and lowest and one that a variable could take.

Visual Representation 

Frequency distribution is a statistical tool that helps people to have a visual representation of information or an observation about a particular thing. Researchers often use this method to visualize the data that they collected as samples. One such example is the calculating height of a set of children. The height of children can be categorized into different ranges. If you measure the height of 40 children, some are tall. Some are short. With the help of visual representation, you can find out the probability of higher frequency and its concentration. 

In calculating such information, one should keep in mind that the most important factor in the calculation is the time interval and that it must not overlap and should contain all possible observations.

Histograms and bar charts are two methods for the visual representation of frequency distribution. We represent data with the help of the x and y-axis, where the x-axis represents the variable that you wish to measure, and the y-axis represents the count of frequency. For example, in the height of children the x-axis will represent the height, and the y-axis will represent the number of children. The column will represent the full number of children that you are observing along with their respective heights that you measure in each interval.

When we represent data with the help of a histogram, we generally show normal distribution, thus meaning that the majority of such occurrences will fall in the middle columns. With such observations, we can say that frequency distribution is a key ingredient to chart normal distribution that shows observation probabilities divided between standard deviations.

Conclusion 

With the help of the above details, you might have now understood “what is frequency distribution”. We can conclude that data that is frequency tabulated is much easier to comprehend than raw data. You can easily calculate mean, median, and standard deviation with the help of such tables. To represent such a distribution, we require the method of histogram and pie chart, but when we deal in larger data, the graph of the histogram is a stepped one and is approximated by a smooth curve. There is no doubt about the usability of frequency distribution, but they are particularly good for assigning the probabilities and in summarising larger data.