Data analysis is the most important part of any research paper. It contains informative data that interpret the collected data through logical and analytical explanations to determine the relationships, trends, or patterns. Data analysis help in visualizing the data in the form of charts, graphs, and tables.
Why analyze data in research?
Analyzing the data in the research is important because researchers have a story to tell or they need to give the solution to the existing problem. It starts from the question which answers the questions through the collection of the data and personal point of view.
The researchers are meant to write a research proposal first. The research proposal help UK to explore the mission and audience vision to find the pattern for writing the research paper. The researchers are required to analyze the data in a clear, concise, relevant, open, and remain unbiased towards unexpected patterns, or results.
Types of data in research
After assigning a specific value to the data there are rare qualities of describing things. And in analyzing the data you need to organize that value, handle, and present it in a required background in order to make it useful. There are many types of data and below are the basic types of data.
When the presented data has words and descriptions then it is called qualitative data. This data can be observed as it is subjective and harder to analyze while performing research, especially in comparison. For instance, the qualitative data represents everything including, taste, experience, opinion, and texture that comes in the circumference of quality. This type of data is collected through personal interviews, groups, or open survey questionnaires.
The data is presented in numerical figures, then we call qualitative data. This data type can be measured, calculated, distinguished, or ranked(Cramer, 2003). For example, the quantitative is in the form of age, cost, rank, weight, scores, length, etc. this type of data can be presented in the form of charts, graphical format, or apply the method of statistical analysis of this data type. The OMS which is Outcomes Management System is the significant source of collecting the numeric data.
In this type of data, the data is presented in the form of groups. However, in categorical data, the object can not be presented in more than one group. For example, a person explaining their living style, smoking habit, marital status, or drinking habit in the survey comes under the categorical data type. To analyze this data the chi-square test is used as it is a standard method.
Reason on data analysis is the toughest part
There are so many things that need to be considered while composing data analysis. It is normal to leave any one requirement. Data analysis tells the story, tests the hypotheses, identifies patterns, correlations, and trends, and visualizes the data. These are a lot of things that sometimes researchers lack to fulfill. As a result, it creates ambiguity in the research and leaves the reader with questions. Following is the reason why data analysis is a difficult part of the research paper for the researcher.
Improper representation of the targeted audience
Inappropriate calculation of the targeted audience is an obstacle in the path of the researcher in achieving its main aims and objectives. The appropriate calculator for the targeted audience is dependent on the probability of observed data. As a result, it leads to miscalculating the probability of observed data and makes the data false.
Lack of resources for collecting data
Data analysis requires a large amount of information including qualitative and quantitative data. But due to a lack of resources, the researchers are unable to collect the large-scale research. Even though many developing countries’ governments, non-government organizations, educational institutions, and public service providers lack knowledge and especially the resources which are needed for quantitative research.
Inability to control the environment
In many cases, researchers find a problem in controlling the environment where the opposition answers the questions in the survey. However, the response depends on the particular time, and time depends on the situation.
Limited results in research
The data analysis process includes a set of questionnaires with close-ended questions. As a result, a research proposal leads to limited outcomes. Due to this results never show the actual occurrence in a generalized form. Moreover, the opposition has limited options for responses due to the selection made by the researcher.
Expensive and time-consuming
The data analysis process is expensive, difficult, and consumes lots of time. Data analysis is the critical part of the research which is carefully planned to ensure the complete randomization and right designation of particular groups. However, the majority of opposition is related to the targeted audience. By doing so, you have a deep drive to get responses to the research. Data collection in data analysis research is often expensive and unapproachable which is against the rule of qualitative and quantitative research.
Difficulty in analyzing the data
The quantitative study of the data analysis requires analysis in the form of statistics which becomes difficult for the researchers who have no mathematical background. Statistical analysis is based on mathematics and scientific discipline which is difficult for the non-statistical to perform.
Therefore, it is a lot more complex for psychology, education, social sciences, and anthropology background researchers. For an effective response, the researcher needs to be more focused on the research problem rather than simply yes or no.
Data analysis is the most crucial part of the research paper and at a time it is the most difficult part to perform. The data analysis is difficult to perform because it requires the data in a statistical form which becomes difficult for the researcher who has zero mathematical background. Moreover, data analysis is the most time-consuming part of the research paper because a researcher needs to find the data by deep-diving into the details, or by conducting surveys. It is expensive because it takes money to get resources ready for conducting a specific survey. Hence, it is necessary for researchers to carefully perform this part of the research paper because the whole paper depends on the data you have collected.