Key Concept Exercise: Following quantitative research designThe data collection process is always a fundamental element in empirical research.For this week’s Key Concept Exercise you will shape your research idea within the context of a quantitative research framework, analyse the optimal data collection process that could align to your research idea, explore the strengths and weaknesses of the chosen technique, and finally critically discuss the potential validity and reliability of the data that you plan to collect.To prepare for this Key Concept Exercise:Read the required Learning Resources for Week 4Return to your chosen research topic-problem identified inWeek 1 (as subsequently amended) and consider a quantitative approach)please note I did not do week 1 assignment as it was not graded but I attached to you the week 1’srequirementto understand what it was about. Alsodo not forget my master is under MarketingTo complete this Key Concept Exercise:By Day 3In approximately 500 words, explain how your research ideas could take the shape of a quantitative research project.In formulating your Key Concept Exercise, consider the following questions:What specific methods would you implement for data collection and analysis?What type of data would you need to tackle the research question(s)?What are the strengths and weaknesses of the research design?Can you recommend ways to maximize the validity and reliability of the data to be collected?By Day 3, submit your Key Concept Exercise to the Turnitin Link provided.When writing your responses you should synthesise the theory with real-world experience and use examples of the theories in action.Be sure to read over your Key Concept Exercise before submitting it to your Instructor. Make sure the spelling and grammar are correct and the language, citing and referencing you use when providing your opinion are appropriate for academic writing.YOU MUST USE ALL THE RESOURCES, following:
Module Text
Collis, J. & Hussey, R. (2013) Business Research: A Practical Guide for Undergraduate and Postgraduate Students. 4th ed. London:
Palgrave-MacMillan.Chapter 10, âCollecting data for statistical analysisâ (pp. 195-224)Chapter 11, âAnalysing data using descriptive statisticsâ (pp. 225-257)
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