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Question ECO 301: Decision-Making Analysis Paper Guidelines and Ru

Question ECO 301: Decision-Making Analysis Paper Guidelines and Ru

Question
ECO 301: Decision-Making Analysis Paper Guidelines and Rubric
Overview
Your final project for this course is a detailed analysis of a specific problem statement. How economic themes, such as demand, production, cost, and market
structure relate to a particular company will be a focus of this analysis. You will analyze these components with quantitative techniques, like regression analysis
and linear programming. You will select a product or service with substantial data. Some possible topics: unemployment and crime
The project is divided into three milestones and a final product, which will be submitted at various points throughout the course to scaffold learning and ensure
quality final submissions. Prompt
Your final project should answer the following prompt: What economic theories and quantitative techniques are used to solve business decision problems and
how are they applicable in real-world settings?
Specifically, the following critical elements must be addressed:
I. Introduction/Statement of Problem
A. What problem are you trying to solve? Discuss the history and key information about the problem and address why the issue/problem is important.
B. Describe the model, hypothesis, and theoretical framework that will be used to explain and forecast variables. The model should be in the form of
functional equations. QD = f(P, Y, …)
C. What data sources do you plan to use? A minimum sample size of 15 is required. Include a complete description of the data sources and assess
their validity, accuracy, creditability, and reliability for the chosen issue. Make sure all data sources are referenced.
D. Which variables are used in the model? Why are they used? Considering the relation among measurable variables, what is the impact of an independent variable X on a dependent variable Y? Are there additional independent variables that could influence variable Y? If so, explain.
E. What assumptions can you make about the data? In your analysis, consider the following: accuracy, consistence, sample as representative of the
population, biased/unbiased, efficient, and weakness of data (currency, not a complete data set, biased, not scientifically accurate).
F. What estimation procedure do you plan to use? If you are using time series data, be sure to account for the identification problem. Why did you
choose is this particular procedure? II. Regression Analysis – Perform a regression analysis on the data.
A. Compute for the following:
1. Standard errors
2. T-stats
3. R2 4. Coefficients, 5% and 1% levels
5. Possible other models to test
III. Computer Output and Evaluation of Results – What are the results of your regression analysis? Include the data you used to estimate the demand
model, the results of your analysis, an analysis of the results, and a description of remaining issues that need to be addressed, i.e. other models to test.
Be sure to include standard errors, t-stats, R2, coefficients, 5% and 1% levels. IV. Statistical Analysis of Results – What are the implications of the t-stats, F test and Adjusted R2? Are they consistent or contradictory? If they seem to be
contradictory, how can this be resolved? V. Conclusion and General Comments – What are key take-a-ways that can be applied in your own personal or professional real-world settings? Provide
concrete or hypothetical examples (if you are not in an applicable field) that support your conclusions. How might this model change in the future given
assumptions? Deliverables
Milestone Deliverables Due in Module Grading Metric 1 Final Project Milestone One: Regression Analysis Practice
Submit your sample regression analysis and statistical test
Final Project Milestone Two: Demand Analysis
Submit your demand analysis
Final Project Milestone Three: Regression Analysis
Submit your project-based regression analysis
Decision Making Analysis Paper
Submit the final version of all portions of your final paper within
a single document. Two Regression Analysis Three Demand Analysis Five Regression Analysis Seven Final Project Rubric 2
3

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