While planning a research strategy and design a researcher faces the option of choosing from various methods, the choice of the correct methods is the basis of a good research design. Research methods implies the methods and tools used in research, research methodology is the rationale behind the choice of particular tools and methods, such rationale is guided by the research objective, type, scope, budget and time constraints, level of accuracy ,etc. For deciding the correct research methodology a researcher must have sound knowledge of research and statistical methods and tools and as well as their assumptions, applications, limitations and relevance. Apt research methodology leads to clarity conciseness, comprehensiveness, logical sequence, simplicity, efficiency, ease in reading, evaluation and information search.

Data analysis is an integral part of any research work because it helps you to arrive at a conclusion based on tested facts and figures in any field including - science, business, social science, education and so on. However, this is just one aspect of looking at it; there are plenty of other benefits also that you get to enjoy by resorting to data analysis.

Benefits of data analysis in research:

• It helps you in remodeling, revising and reviewing the structure of your paper based on the findings of various sources.
  
• By analyzing data, you can divide one major problem into different parts for the ease of resolution and approach.
  
• Data analysis lends you a vast insight into any particular topic by filtering down meaningful information or pieces of relevant details.
  
• Data collection only involves gathering of plenty of information, whereas data analysis creates a foundation for critical decision.
  
• With the help of data analysis, you can prepare your entire dissertation proposal, which is otherwise not possible.
  

Since data analysis gives you an access to full-proof statistical process, you know your work is free of any bias. It gives you an opportunity to base your research on valid qualitative and quantitative findings. Considering all this, there is no doubt in admitting the fact that data analysis is important for both the research and the researcher. 

While there are several demarcations between the two approaches of study, the methods of analyzing data also differ. Here’s a brief discussion on these methods:

• Quantitative methodology:

o Regression analysis is one of the fundamental quantitative methods of research existing for the researchers. The advanced array of experimental techniques is reliant on this methodology.

o Vector Auto-regression analysis is among the highest array of quantitative techniques present today. This methodology is mostly used for setting up contributory association amid the variables beneath inspection.

o Matrix Algebra analysis is a fundamental method for demonstration of data which helps the researchers to examine the complete set of panel or cross-section data more effectually.

• Qualitative methodology:

o Factor analysis is one of the best method for scrutinizing the strength and reliability of any questionnaire that have been used for survey method. It examines the factors in any questionnaire on the basis of the objective of the study. It condenses the idleness of the questionnaire.

o Box plot analysis is a precise technique for expressing the data in provisions of its variety, mean and discrepancy. It represents an evocative statistics in case of any variable.

o Interview coding is an explicit method which is used for examining the interviews. Particular keywords and recurring words are illustrated in the interview which being identified is associated with the ontology of the research that will be carried out.