comparing models to assess the research problem case

Remember our research project for this is social media marketing in small business

Module 5 – Case

Comparing Models to Assess the Research Problem

Assignment Overview

In this Case Assignment, you will be reading several articles and sources relating to different kinds of data analysis, the process of inferring conclusions from data, the legitimacy of different kinds of analyses, and the development of conclusions and recommendations from your data. You will then be asked to develop a preliminary data analysis and presentation plan, describing the kinds of inferences you hope to draw from your data and how you justify their legitimacy. You also be asked to sketch out a plan for presenting your findings for your research site and wrapping up your relationship with the site.

As the course has progressed, you have made a series of decisions in which you have increasingly specified the structure of your project. These decisions build on each other in critical ways. However, you’re not locked into previous decisions if you subsequently decide you need to change direction. As before, you have an opportunity to go back and revise and/or extend the sections completed in previous modules. If you do revise earlier sections, please include them and indicate what changes you have made to them. Case grades given for the first four modules have been advisory rather than final. Your ultimate grade will be based on the completed methodology section represented by the final versions of all five cases put together at the end of the course here in Module 5.

Case Assignment

Prepare a 5- to 7-page paper in accordance with the following Assignment Expectations, describing the analysis issues for your project that form the basis for the Methodology section of your dissertation, in accordance with the following outline:

  1. Identify the major kinds of data that you plan to collect during your project. Discuss the IRB approval process. For each major kind of data, identify steps that you will take to analyze those data for purposes of the project. The readings will help you identify different kinds of data and appropriate analytical procedures associated with each.
  2. Identify the main kinds of conclusions that you hope to draw from your data analysis. These might be descriptive/analytical, prescriptive in the form of recommendations, suggestions in the way of forward thinking, or some combination of these. For each type of conclusion, identify offices and people within the organization that you believe might be interested in your conclusions, and why they might be interested.
  3. Identify the main deliverables from your project, and to whom the delivery would be made other than the members of your doctoral committee.

Remember, the five Case Assignments that you’ve completed in this course together constitute an effective first draft of the Methodology section of your project proposal. Therefore, you want to review the previous assignments carefully in light of the feedback that you have been given and take the opportunity to make any needed revisions or modifications so that the document hangs together clearly and effectively. Your final grade for the case part of this course will be based on the sum of the five parts taken together, so this is your opportunity to remediate any deficiencies you might have encountered in previous modules.

Please conclude your paper with a paragraph or two assessing the effectiveness of this approach to developing the methodology for your project and any lessons that you have learned during this course about the nature and conduct of academic research in applied settings.

Assignment Expectations

Length: The written component of this assignment should be 5–7 pages long (double-spaced) without counting the cover page and reference page.

Organization: Subheadings should be used to organize your paper according to the questions.

Grammar and Spelling: While no points are deducted for minor errors, assignments are expected to adhere to standard guidelines of grammar, spelling, punctuation, and sentence syntax. Points may be deducted if grammar and spelling impact clarity. We encourage you to use tools such as and proofread your paper before submission.

When you write your paper make sure you do the following:

  • Answer the assignment questions directly.
  • Stay focused on the precise assignment questions. Do not go off on tangents or devote a lot of space to summarizing general background materials.
  • Use evidence from your readings to justify your conclusions.
  • Be sure to cite at least five credible resources.
  • Make sure to reference your sources of information with both a bibliography and in-text citations. See the Student Guide to Writing a High-Quality Academic Paper, including pages 11-14 on in-text citations. Another resource is the “Writing Style Guide,” which is found under “My Resources” in the TLC Portal.

Your assignment will be graded using the following criteria:

Assignment-Driven Criteria: Student demonstrates mastery covering all key elements of the assignment.

Critical Thinking/Application to Professional Practice: Student demonstrates mastery conceptualizing the problem, and analyzing information. Conclusions are logically presented and applied to professional practice in an exceptional manner.

Business Writing and Quality of References: Student demonstrates mastery and proficiency in written communication and use of appropriate and relevant literature at the doctoral level.

Citing Sources: Student demonstrates mastery applying APA formatting standards to both in-text citations and the reference list.

Professionalism and Timeliness: Assignments are submitted on time.

Module 5 – Background

Comparing Models to Assess the Research Problem

Required Reading

EvaSys. (2018). How to effectively carry out a qualitative data analysis. Retrieved May 10, 2018, from

Reporting and discussing your findings. (2018). Retrieved May 10, 2018, from the Monash University website at

Data presentation and analysis. (2018). Retrieved May 10, 2018 from the Planning Tank website at

Research data management system project: Best practices in research data management. (2018). New England Collaborative Data Management Curriculum. Retrieved May 10, 2018.

Rowley, J. (2002). Using case studies in research. Management Research News, 25(1), 16-27. Retrieved May 10, 2018. Available in the Trident Online Library. (Search by title and author’s last name.)

Stockberger, D. (2016). Introductory statistics: Concepts, models, and applications. Missouri State. Retrieved from

Brown, N., Lave, B., Romey, J., Schatz, M., & Shingledecker, M. (2018) Beginning Excel. OpenOregon, Creative Commons License. Retrieved from and

Book II: Chapters 1–4 and
Book V: Chapter 1 in:
Harvey, G. (2016). Excel 2016 All-in-One For Dummies. John Wiley & Sons. Available in the Trident Online Library: Follow these instructions for Finding Skillsoft Books. Enter 112925 in the search bar.

Video Material

ExcellsFun. (2012, October 19). Excel data analysis: Sort, filter, PivotTable, formulas (25 examples): HCC Professional Day 2012 [Video file]. Retrieved from

Gibbs, G. R. (2015, March 4). Quality in qualitative research [Video file]. Retrieved from

Curry, L. (2015, June 23). Fundamentals of qualitative research methods: Data analysis (module 5) [Video file]. Retrieved from

Russell, D. (2014, October 24). Introduction to quantitative data analysis [Video file]. Retrieved from

McGinn, J., Kaniasty, E., Mistry, D., Soucy, K., & Snyder, C. (2012). Delivering results: How do you report user research findings? New Hampshire Usability Professional’s Association Meeting. Retrieved from

Sampling and Data

Gibbs, G. R. (2012, October 24). Social surveys. Part 1 of 2 on surveys and sampling [Video file]. Retrieved from

Gibbs, G. R. (2012, October 24). Sampling. Part 2 of 2 on surveys and sampling [Video file]. Retrieved from

Gibbs, G. R. (2014, March 11). Crosstabulations and their interpetation. Part 1 of 2 on crosstabulations and chi-square [Video file]. Retrieved from

Gibbs, G. R. (2014, March 11). The chi-square statistic and reporting results. Part 2 of 2 on crosstabulations and chi-square [Video file]. Retrieved from

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