- •Describe the basic methods of economic research.
- •Describe the major types of research.
- •Give a description of the analysis and synthesis.
- •Give the description of the method of knowledge and presentation. Scientific abstraction.
- •Describe the structure of the thesis.
- •Describe the basic principles of writing a scientific article.
- •Methods of collection and analysis of information sources for writing a research paper.
- •8. Describe the inductive and deductive methods of cognition.
- •Induction
- •Basic principles of modeling method.
- •Rules for writing a scientific article.
- •11. Describe modern methods of analysis of information for scientific writing.
- •12. Describe abstraction as a method of economic research.
- •13. Describe the method of mathematical and statistical analysis.
- •1. Mean
- •2. Standard Deviation
- •3. Regression
- •4. Sample Size Determination
- •5. Hypothesis Testing
- •14. Give a description of the basic terminology used in the writing of scientific papers.
- •15. Describe the dialectical method in the economy.
- •16. The structure and rules of writing an essay.
- •Include a Purposeful Conclusion
- •17. Describe the basic features of an essay.
- •18. Describe the four levels of academic writing in English.
- •19. The nature, structure and functions of economic methodology
- •20. Describe the main types of scientific papers.
- •21. Essay: “my master’s thesis” How do I Choose a Master’s Thesis Topic?
- •Talk with Your Advisor
- •Think About Your Interests
- •Look at a Topic You Can Test
- •Check Journals and Publications
- •22. Essay: “The basic rule in choosing the theme of scientific work”
- •23. Essay: “modern problems of scientific research”
- •24. Essay: “Describe the current sources of information for scientific writing”
- •25. Essay: “The use of information technology in the writing of scientific papers”
- •26.Essay “ Passage of Anti-Plagiarism, citing the rules”
- •27. Essay”Formulation of the problem in the writing of scientific work”
- •28. Essay”Describe the main challenges in the writing of the thesis”
- •29. Essay” The structure of the thesis and its writing rules”
- •Introduction
- •30. Essay”Problems arising from the data collection”
30. Essay”Problems arising from the data collection”
The errors manifest themselves during data collection can be divided into two groups · Errors in the sample. They are related to mismatch of the study sample and the general population. · Systematic errors. This group includes all the other errors that are not sampling errors. They result from imperfect or logic concept studies misinterpretation of responses and errors in the processing stage, data analysis and presentation. Systematic errors are divided into two types: · Random. Such errors lead to deviations from the true value to a random value and a random direction. · Accidental. Such errors lead to one-sided deviation of the results from the true value. Systematic errors are more dangerous than the error in the sample: they are more difficult to measure, in addition, an increase in the sample does not always allow them to cut. The amount of bias may exceed ten times the sampling error and turn research results almost nothing. Systematic errors can be reduced. However, such reductions are the tools do not increase the number of samples, and special techniques. To properly applied, it is necessary to identify the main sources of systematic error. There are two main types of systematic error sources of their occurrence: Bug unobserved; Bug surveillance. Unobserved error associated with the inability to obtain data from the elements of the study population. This error can occur for two main reasons: · Part of the object of study is not represented in the sample (non-coverage error); · Elements of the sample did not provide data (non-response error due to lack of on-site or failure of the interview). The error occurs when non-compliance monitoring data on a set of elements presented in the report, the true values. This discrepancy may occur in the following circumstances: · Providing incorrect data elements; · Incorrect registration data;
· Error in the processing, analysis and presentation of research results.