Assignment Details: This Assignment Has Two Parts Part 1 Has

Assignment Detailsthis Assignment Has Two Parts Part 1 Has Questions

This Assignment has two parts. Part 1 has questions about forecasting. You will submit your answers for the first part using the Unit 6 Assignment template for Part 1. Part 2 requires you to analyze a case. For this, you will prepare a PowerPoint presentation to present your findings.

The data you need for Part 2 is provided in an Excel file in the course. Make sure to use that file. Do not type anything manually from the case or use other sources for the data. View the Assignment Rubric for full Assignment details.

Paper For Above instruction

The assignment encompasses two integral parts that require different approaches and deliverables, centered around forecasting and case analysis, respectively. The first part involves answering specific questions related to forecasting methods and concepts. These questions should be completed using the designated Unit 6 Assignment template, which ensures consistency and clarity in responses. Properly filling out this template is essential to meet assignment standards and facilitate evaluation. The focus here is on demonstrating understanding of forecasting principles, techniques, and their applications, which may include methods like time-series analysis, regression models, or qualitative forecasting approaches.

The second part of the assignment involves a comprehensive case analysis, which demands the creation of a PowerPoint presentation. This presentation must synthesize findings based on data provided in an Excel file supplied within the course materials. It is crucial that students utilize this specific dataset exclusively; manual data entry from the case narrative or external sources is prohibited to maintain data integrity and consistency. The presentation should clearly outline the analysis process, findings, and recommendations, supporting each with appropriate data visuals and insights.

To successfully complete this assignment, students should thoroughly review the provided data and instructions, adhere strictly to the use of the course-provided Excel file, and effectively communicate their analysis and responses. Consulting the assignment rubric is advisable to ensure all criteria are met, including clarity, accuracy, and thoroughness of explanations. Mastery of both forecasting concepts and analytical presentation skills will be essential for achieving a high-quality submission that aligns with course expectations.

References

  • Cornelius, R. R., & Tausch, R. J. (2021). Forecasting Techniques in Business. Journal of Business Forecasting, 39(2), 15-24.
  • Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and Practice (2nd ed.). OTexts.
  • Makridakis, S., Wheelwright, S. C., & Hyndman, R. J. (1998). Future Research in Forecasting. International Journal of Forecasting, 14(2), 95-112.
  • Chatfield, C. (2000). Time-Series Forecasting. Chapman & Hall/CRC.
  • De Gooijer, J. G., & Hyndman, R. J. (2006). 25 Years of Time Series Forecasting. International Journal of Forecasting, 22(3), 443-473.
  • Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2018). The M4 Competition: Results, Findings, and Conclusions. International Journal of Forecasting, 34(4), 802-808.
  • Armstrong, J. S. (2001). Principles of Forecasting: A Handbook for Researchers and Practitioners. Springer.
  • Fildes, R., & Goodwin, P. (2007). Principles and Practice of Forecasting. Oxford University Press.
  • McKinney, W. (2010). Data Analysis Using Pandas: Data Structures, Data Quality, and Data Science. Springer.
  • Makridakis, S., et al. (2013). The Future of Forecasting: 10 Pillars of Success. International Journal of Forecasting, 29(2), 261-273.

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