28 Jun BUS461: Decision Modeling & Analysis
During the course, you have applied a variety of methods to analyze data sets and uncover important information used in decision making. Having a good understanding of these topics is important to be able to apply them in real-life applications. Below are some of the key elements that were discussed throughout this course. Analyze each of the elements below. In your analyzation, consider and discuss the application of each of these course elements in analyzing and making decisions about data. Incorporate real-life applications and scenarios.
The course elements include:
- Probability
- Distribution
- Uncertainty
- Sampling
- Statistical Inference
- Regression Analysis
- Time Series
- Forecasting Methods
- Optimization
- Decision Tree Modeling
The paper must (a) apply and reference new learning to each of the ten course elements, (b) build upon class activities or incidents that facilitated learning and understanding, and (c) present specific current and/or future applications and relevance to the workplace for each of the ten course elements. The emphasis of the paper should be on modeling applications, outcomes, and new learning.
The paper
- Must be 2100-2500 words (excluding title page and references page), double-spaced, and formatted according to APA style.
- Must include a separate title page with the following:
- Title of paper
- Student’s name
- Course name and number
- Instructor’s name
- Date submitted
- Must use at least three scholarlysources in addition to the course text.
- The Scholarly, Peer Reviewed, and Other Credible Sources table offers additional guidance on appropriate source types. If you have questions about whether a specific source is appropriate for this assignment, please contact your instructor. Your instructor has the final say about the appropriateness of a specific source for a particular assignment.
- Must document all sources in APA style.
- Must include a separate references page that is formatted according to APA
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