Last Updated on December 9, 2022 by
Analytical methods are critical to solving sustainability issues as current approaches appear insufficient. Analytical methods are simple, intuitive and based on how analysts handle the issues in academic research. Initially, the researcher can choose an analytical method to identify the issue. Secondly, there is a need to choose an accurate approach. Depending on the issues and situations, the nature of the approach is varied.
7 Things to Do in Academic Research
In academic research, the analytical methods are based on generic processing. It combines the scientific method with formal processing to find the solutions to research problems. There are several points to note about the use of analytical methods in academic research. The following seven things are highly significant:
Problem Identification
Problem identification is one of the key parts of the analytical methods. It serves as the major identifier and evaluator of the academic research problem. At the same time, it explores the solution possibilities. In academic research, the problem identification step can be used to explore the core issue. If the research finds the root problem, the chances of solutions may be high. Problem identification allows the academic researcher to use a multi-methods’ approach to comprehend the root problem in the research further. It is used to gather information so the actual issue can be resolved. Problem identification is a highly important step and provides the base of the solution. Therefore, you must get PhD dissertation help for problem identification.
Choosing the Solution Approach
It is called the most important phase in analytical methods. All potential working for the solution of an academic research problem is based on the solution approach. The researcher can choose several approaches to solve the issue; however, the selection must be based on the problem’s nature, scope and potential. At this stage, the research needs to decompose the issue in the right direction and find the root cause. Similarly, proper identification is required to find the main causes of every sub-problem and the appropriate solutions.
The Process of Hypothesize Analysis
Hypothesizing analysis in analytical methods is speculative of the connection between two or more than two variables. Basically, it is a prediction based on the researcher’s expectations about the study solution. The process of hypothesizing analysis is further divided into several sub-heads, such as:
- Question Formation
- Background Research
- Creating a specific Hypothesis
- Experimental Designs and Data Collection
- Result Analysis
In analytical methods, hypothesis analysis is just forecasting. However, it considers more than that in several cases. It initiates with a specific question which is further based on the academic research background. At this point, the researcher can easily establish a testable hypothesis. Similarly, when the hypothesis is the source of prediction only, the research goal is to establish whether the prediction is correct or not. In the experiment, the researcher must explore all factors to regulate an accurate source, with the reason to use that source.
Design of Experiment
Design of Experiment or DOE in analytical methods is used for systematic product optimization. The use of the design of experiments when the researcher is working with multifactorial experiments is highly important in academic research. It can use to identify the ideal solutions. Furthermore, it supports maintaining the rational factor-response connections and stipulates augmented comprehension of variability sources. The design of experiment application holds several tools in the development of analytical methods by performing minimal investigation to reveal maximum information and saving costs, efforts and time. The design of the experiment was initially formed by Ronald Fisher, and it can be useful for the following objectives:
- Identifying the relationship and effect of a factor or several factors on the output/response
- Understanding the interaction of factors in effect
- Factors functioning and the behaviour of the response
- Response optimization
The design of the experiment can also be helpful in blocking, randomization, replication, and factorial principles of systematic production designs. Establishing and examining these designs are based on manual calculations. These calculations are now computerized to make them more effective.
Performing the Experiment
In analytical methods, several approaches are there to perform the experiment. The collection of data is required to maintain the targeted population in academic research. Experimental performance through participative data can be utilized through the application of different methodologies. There are different methods of data collection in research studies, such as the subject pool system. Through the system, students or groups of students can be enrolled for data participation. Students and other participants can sign up to contribute; it is possible through both online and manual systems. Publishing a proper advertisement is also possible to get the participants’ consent.
The Output of Hypothesis and its Acceptance or Rejection
In academic research, the tabulated value is high as compared to the calculated value. It can create the acceptance or rejection cause of the hypothesis. Another approach to hypothesis output is the probability value approach. The hypothesis is based on the researcher’s predictions only. In case the null hypothesis may not be supported, there is a rejection on the basis of probability; in this situation, the researcher needs to accept the alternative hypothesis. On the contrary, in case the sample does not show any contradiction in the hypothesis, it may be accepted.
Solution Implementation
Solution implementation is highly significant in analytical methods. Incorporating the research implementation is helpful in the program evaluations. It can support evaluating programs fairly and accurately to learn the overall program components. The researcher may be capable of generating evidence-based programs more effectively and in efficient ways.
Conclusion
Several important points are there to maintain the analytical methods more effectively. Analytical methods focus on the comprehension of the relationship of cause and effect between two variables. The researcher needs to be focused on the abovementioned seven things when he/she tries to implement analytical methods in the research. Analytical methods can also be effective in risk assessment, equivalence and management. It supports the development of acceptance or rejection criteria on the basis of experiments.
