Whereas, a frequency distribution is generally the graphical representation of the frequency table. Question 2: Discuss the differences between the frequency table and the frequency distribution table?Īnswer: The frequency table is said to be a tabular method where each part of the data is assigned to its corresponding frequency. Here, we have a uniform class size, which is equal to 5 (5 – 0, 10 – 5, 15 – 10, 20 – 15 are all equal to 5). The class size is the difference between the lower and upper class-limits.The classmark is defined as the average of the upper and lower limits of a class.10-15 are 10 (lower limit) and 15 (upper limit). The class limits of the third class, i.e.The lower limit of the first class interval i.e.The lower limit of the first class interval.Question 1: The following is the distribution for the age of the students in a school: Age The frequency distribution can be done for disjoint data as well, similar to how it is done above. An example of such as case would be 0-4, 5-9, 10-14, and so on. For example, if we had a student who has scored 5 marks in the test, his marks would be included in the class interval 5-10 and not 0-5.Īnalogous to continuous class intervals are disjoint class intervals. Note that in continuous cases, any observation corresponding to the extreme values of a class is always included in that class where it is the lower limit. This example is a case of continuous class intervals as the upper limit of one class is the lower limit of the following class. The lowest number in a class interval is called the lower limit and the highest number is called the upper limit. The first column here represents the marks obtained in class interval form. Take a look at the table below to understand the concept better: Marks obtained in the test (Class Interval) Such tables take into consideration groups of data in the form of class intervals to tally the frequency for the data that belongs to that particular class interval. Learn more about Range and Mean for Grouped Data here in detail. In this case, we use what is called a grouped frequency distribution table. Besides, the table we will obtain will be very large in length and not understandable at once. It becomes difficult to tally for each and every score of all 100 students. Now consider the situation where we want to collect data on the test scores of five such classes i.e. It takes into account ungrouped data and calculates the frequency for each observation singularly. Read more about Bar Graphs and Histograms here in detail.Ī frequency distribution such as the one above is called an ungrouped frequency distribution table. Here, the total we have obtained after tallying the test scores of the students is 20 which is also the number of observations given. Also, note that your frequency must always total the number of observations after tallying. In the example above, the frequency refers to the number of students getting a particular mark in the test. The table below will help you understand this better: Marks obtained in the test Hence, in case of repetitions, the frequency increases. Note that the term frequency refers to the number of times an observation occurs or appears in a data set. It is for this reason that we organize larger data into a table called the frequency distribution table. The objective of statistical interpretation is to organize data into a concise form so that interpretation and analysis become easy. If we were to include the test scores of all 20 students in this class, it would be very difficult to understand and interpret such data unless it is ‘organized’. Now, imagine how difficult and cumbersome this process would get if there were a larger number of observations. It is the difference between the largest and smallest values of a data set. A statistical measure called range can be defined. We consider the marks obtained by ten students from a class in a test to be given as follows: To understand frequency distribution, let us first start with a simple example. Range and Mean Deviation for Ungrouped Data.Range and Mean Deviation for Grouped Data.Hence, statistics is a very useful tool to study data.ĭownload the Cheat Sheet of Statistics by clicking on the button below Trends can be studied and results can be drawn from data interpretation. It is useful in understanding what a dataset reveals about a particular phenomenon. Statistics refers to the collection, organization, distribution, and interpretation of data or a set of observations.
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