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Project Format

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1. Introduction: In this section (of about an A4 size page, or less, in two to three paragraphs), you will first give a brief highlight of the principal activities of the organization where the project is being carried out; their prime goal; their position today in the particular business or sector; major opportunities and constraints they are facing ; major strengths and weaknesses. Then you will give a one or two sentence statement of what the company desires you to study (or address) in this project, or what they agree to let you study (the broad intent).
2. Project Objectives: In this section, you will delineate, as precisely as possible, the specific objectives of the project, using perhaps bullet style. The stated objectives should be consistent with the “broad intent” mentioned in Sec. The objectives should reflect an underlying principle / concept.
3. Scope: Relative to the objectives stated above, here you would explicitly specify the delimiting aspects, if any, that would define the scope of the current study. For example, if the study concerns “employee motivation,” and if it is agreed that only employees from production functions are to be studied, the scope would be restrictive to all the employees of the production function. If there are more plants than one, and if it is agreed that only a specified plant’s production function employees would be covered, then this would be a restriction. All such aspects would define the specific scope of the project.
4. Methodology: This section must explain your detailed plan for conducting project, covering sampling logic, data collection, questionnaire etc., and analysis plan
5. Analysis: The data collected will have to be coded and classified according to the research requirements and then analysed. A qualitative or quantitative analysis can be employed. In quantitative analysis descriptive statistics and inferential statistics can be used. Univariate and multi-variate techniques can be used depending on the number of variables studied.
6. Limitations: Possible limitations of your work in terms of sampling, missing data, explanatory power of models etc.

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