Statistics deals with the collection, presentation and analysis of the data, as well as drawing meaningful conclusions from the given data. Generally, the data can be classified into two different types, namely primary data and secondary data. If the information is collected by the investigator with a definite objective in their mind, then the data obtained is called the primary data. If the information is gathered from a source, which already had the information stored, then the data obtained is called secondary data. Once the data is collected, the presentation of data plays a major role in concluding the result. Here, we will discuss how to present the data with many solved examples.
What is Meant by Presentation of Data?
As soon as the data collection is over, the investigator needs to find a way of presenting the data in a meaningful, efficient and easily understood way to identify the main features of the data at a glance using a suitable presentation method. Generally, the data in the statistics can be presented in three different forms, such as textual method, tabular method and graphical method.
Presentation of Data Examples
Now, let us discuss how to present the data in a meaningful way with the help of examples.
Example 1:
Consider the marks given below, which are obtained by 10 students in Mathematics:
36, 55, 73, 95, 42, 60, 78, 25, 62, 75.
Find the range for the given data.
Solution:
Given Data: 36, 55, 73, 95, 42, 60, 78, 25, 62, 75.
The data given is called the raw data.
First, arrange the data in the ascending order: 25, 36, 42, 55, 60, 62, 73, 75, 78, 95.
Therefore, the lowest mark is 25 and the highest mark is 95.
We know that the range of the data is the difference between the highest and the lowest value in the dataset.
Therefore, Range = 95-25 = 70.
Note: Presentation of data in ascending or descending order can be time-consuming if we have a larger number of observations in an experiment.
Now, let us discuss how to present the data if we have a comparatively more number of observations in an experiment.
Example 2:
Consider the marks obtained by 30 students in Mathematics subject (out of 100 marks)
10, 20, 36, 92, 95, 40, 50, 56, 60, 70, 92, 88, 80, 70, 72, 70, 36, 40, 36, 40, 92, 40, 50, 50, 56, 60, 70, 60, 60, 88.
Solution:
In this example, the number of observations is larger compared to example 1. So, the presentation of data in ascending or descending order is a bit time-consuming. Hence, we can go for the method called ungrouped frequency distribution table or simply frequency distribution table. In this method, we can arrange the data in tabular form in terms of frequency.
For example, 3 students scored 50 marks. Hence, the frequency of 50 marks is 3. Now, let us construct the frequency distribution table for the given data.
Therefore, the presentation of data is given as below:
|
Marks |
Frequency (Number of students) |
|---|---|
|
10 |
1 |
|
20 |
1 |
|
36 |
3 |
|
40 |
4 |
|
50 |
3 |
|
56 |
2 |
|
60 |
4 |
|
70 |
4 |
|
72 |
1 |
|
80 |
1 |
|
88 |
2 |
|
92 |
3 |
|
95 |
1 |
|
Total |
30 |
| Also, read: |
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The following example shows the presentation of data for the larger number of observations in an experiment.
Example 3:
Consider the marks obtained by 100 students in a Mathematics subject (out of 100 marks)
95, 67, 28, 32, 65, 65, 69, 33, 98, 96,76, 42, 32, 38, 42, 40, 40, 69, 95, 92, 75, 83, 76, 83, 85, 62, 37, 65, 63, 42, 89, 65, 73, 81, 49, 52, 64, 76, 83, 92, 93, 68, 52, 79, 81, 83, 59, 82, 75, 82, 86, 90, 44, 62, 31, 36, 38, 42, 39, 83, 87, 56, 58, 23, 35, 76, 83, 85, 30, 68, 69, 83, 86, 43, 45, 39, 83, 75, 66, 83, 92, 75, 89, 66, 91, 27, 88, 89, 93, 42, 53, 69, 90, 55, 66, 49, 52, 83, 34, 36.
Solution:
Now, we have 100 observations to present the data. In this case, we have more data when compared to example 1 and example 2. So, these data can be arranged in the tabular form called the grouped frequency table. Hence, we group the given data like 20-29, 30-39, 40-49, ….,90-99 (As our data is from 23 to 98). The grouping of data is called the “class interval” or “classes”, and the size of the class is called “class-size” or “class-width”.
In this case, the class size is 10. In each class, we have a lower-class limit and an upper-class limit. For example, if the class interval is 30-39, the lower-class limit is 30, and the upper-class limit is 39. Therefore, the least number in the class interval is called the lower-class limit and the greatest limit in the class interval is called upper-class limit.
Hence, the presentation of data in the grouped frequency table is given below:
|
Class Interval (Marks) |
Frequency ( Number of students) |
|---|---|
|
20 – 29 |
3 |
|
30 – 39 |
14 |
|
40 – 49 |
12 |
|
50 – 59 |
8 |
|
60 – 69 |
18 |
|
70 – 79 |
10 |
|
80 – 89 |
23 |
|
90 – 99 |
12 |
|
Total |
100 |
Hence, the presentation of data in this form simplifies the data and it helps to enable the observer to understand the main feature of data at a glance.
Practice Problems
-
- The heights of 50 students (in cms) are given below. Present the data using the grouped frequency table by taking the class intervals as 160 -165, 165 -170, and so on. Data: 161, 150, 154, 165, 168, 161, 154, 162, 150, 151, 162, 164, 171, 165, 158, 154, 156, 172, 160, 170, 153, 159, 161, 170, 162, 165, 166, 168, 165, 164, 154, 152, 153, 156, 158, 162, 160, 161, 173, 166, 161, 159, 162, 167, 168, 159, 158, 153, 154, 159.
- Three coins are tossed simultaneously and each time the number of heads occurring is noted and it is given below. Present the data using the frequency distribution table. Data: 0, 1, 2, 2, 1, 2, 3, 1, 3, 0, 1, 3, 1, 1, 2, 2, 0, 1, 2, 1, 3, 0, 0, 1, 1, 2, 3, 2, 2, 0.
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