To write a clear, lucid and practical research methods and data analysis chapter, shou first need to clarify the following points:
1. Define the purpose of the study: figure out what exactly you want to study, whether it is a new point of view or a specific problem.
2. Collect research data: you can look for relevant data through the National Bureau of Statistics, China Statistical Yearbook and other websites to gain an in-depth understanding of the background of the study.
3. Select research method: According to the purpose of the research and the collected data, choose the appropriate research method, such as literature research method, experimental method, observation method or survey method, etc. Each method has its advantages and disadvantages.
4. Collecting data: Use appropriate methods to collect data, such as questionnaires, experiments or observations. When asking questions, make sure that the questions are clearcomprehensively and select data according to the questions.
5. Analyse the data: choose the appropriate method of analysis according to the question and the type of data, such as statistical analysis, case study or comparative study. Be sure that the data are accurate and valid, and correct them in time if there are problems.
6. Findings: Describe the results of the data analysis and tell the reader what the results are. When summarising and evaluating the results, choose from tables, graphs or text.
In the process of writing, you need to pay attention to the following points:
1. make it easy for the reader to understand your thinking and process.
2. make each section relevant to the purpose of the study and the question.
3. use simple and understandable language and avoid overly complex words and statements.
4. scientific and rigorous is very important, pledge your results to be true and reliable.
5. cite enough references to show your research basis and theoretical background.
By following the above steps and precautions, you will be able to write a clear, lucid, and practical chapter on research methods and data analysis.
