Understanding the graphical representation of data in research

This Power Point Presentation has been made while referring to the research books written by eminent, renowned and expert authors as mentioned in the references section. The purpose of this Presentation is to help the research students in developing an insight about the Graphical Representation of Data in Research. I hope the students will find this presentation useful for them.

1. Understanding The Graphical Representation of Data in Research By Dr. Shaloo Saini Assistant Professor MKCE, C T Group of Institutions, Jalandhar Punjab

2. Graphs are very useful tool to present the data. Graphs depicts the mathematical relationship between the variables under study. Graphs present a clear pictorial view of Data and helps in understanding the relationship between the variables depicted through it. There are a variety of Graphs but the popular ones are the Graphs of Time Series and the Graphs of Frequency Distribution. Graphical Representation of Data

3. Classification of Graphs

4. These are also called Line Graphs. These are used to represent the different values of a variable at different points of Time. The ‘X’ axis represents the Time and the ‘Y’ axis represents the variable. Graphs of Time Series

5. Year Production of Rice (in Kg) 2001-2002 65 2002-2003 73 2003-2004 80 2004-2005 40 Line Graph

6. Year Import Export 1980 14 15 1990 20 25 2000 10 15 2010 25 30 2020 40 45 Range Chart

7. A Frequency Distribution can be represented in a graphical manner as: Histogram Frequency Polygon Smoothened Frequency Curve Ogive Graphs of Frequency Distribution

8. It is also called column graph. It have a set of vertical Bars whose area is proportional to the frequencies presented. The ‘X’ axis represents the variable and the ‘Y’ axis represents the frequency. If the class interval is equal then the width of Histograms will be same but if the class intervals is unequal the width of Histograms will change. However the smallest class interval will be taken as the reference class. Histogram

9. Histogram

10. A Frequency Polygon is a Group created by joining the mid points of Histogram. Frequency Polygon can also be prepared with the mid points of Class Interval and Frequencies corresponding to it. The Frequency Polygon is closed at both the ends by joining the Base Line Frequency Polygon

11. Frequency Polygon

12. It is drawn freehand. The main purpose of Smoothened Frequency Curve is to remove accidental variation. The area under the curve is approximately equal to the Frequency Polygon. Smoothened Frequency Curve

13. Smoothened Frequency Curve

14. It is also called Cumulative Frequency Curve. These are used when the researcher wants to know the number of items whose values are more than or less than a certain amount. Therefore it can be made using less than or more than method. If the researcher wants to know the number of items that are less than a particular size then the Cumulative Frequencies are developed from least to the greatest. If the researcher wants to know the number of items that are more than a particular size then the Cumulative Frequencies are developed from greatest to the least. Ogive

15. Ogive

16. Graphs are very effective means to present the data while explaining the mathematical relationship between the variables. There are a variety of Graphs but the popular ones are the Graphs of Time Series and the Graphs of Frequency Distribution. The Graphs of time series can be in form of simple line graphs as well as range graphs. Whereas the Graphs of frequency distribution can be in form of Histograms, Frequency Polygon, Smoothened Frequency curve and Ogive. The decision related to the selection of suitable graphs depends upon the nature of study and the type of data. However precision must be ensured in the preparation of Graphs because the Graphs provide a glimpse about the relationship between variables and the results of the study. Summary

17. Bajpai  N. (2015). Data Analysis and Presentation. In  Business research methods . Nodia : Pearson Education. Gupta S.K. & Rangi P.(2017). Data Processing. In Research Methodology (4 th ed., pp9.1-9.28).Punjab: Kalyani Publishers(India). Kothari C. R. & Garg G.(2019). Data Preperation . In Research Methodology Methods and Techniques ( 4 th ed., pp.114-128) New Delhi: New Age International Publishers(India). References

18. This Power Point Presentation has been made while referring to the research books written by eminent, renowned and expert authors as mentioned in the references section. The purpose of this Presentation is to help the research students in developing an insight about the Graphical Representation of Data in Research. I hope the students will find this presentation useful for them. All the Best Dr. Shaloo Saini