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Pages:
9 pages/β‰ˆ2475 words
Sources:
4 Sources
Style:
APA
Subject:
Mathematics & Economics
Type:
Essay
Language:
English (U.S.)
Document:
MS Word
Date:
Total cost:
$ 38.88
Topic:

Decision Modeling & Analysis: Probability, Distribution, Uncertainty

Essay Instructions:

The Final Paper provides you with an opportunity to integrate and reflect on what you have learned during the class.
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 2000-2500 words (excluding title page and references page), double-spaced, and formatted according to APA style as outlined
• Must include a separate title page with the following:
o Title of paper
o Student's name
o Course name and number
o Instructor's name
o Date submitted
• Must use at least three scholarly sources in addition to the course text.
o The Scholarly, Peer-Reviewed, and Other Credible Sources (Links to an external site.)Links to an external site. 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 as outlined
• Must include a separate references page that is formatted according to APA style as outlined
References
Albright, S. Christian; Winston, Wayne L.. Business Analytics: Data Analysis & Decision Making

Essay Sample Content Preview:

Decision Modeling & Analysis
Name
Course name
Instructors’ name
Date
Decision Modeling & Analysis
Making decisions can be challenging, whether we make fast or slow decisions, the process of analyzing information is important because making an informed decision means analyzing all the alternatives before arriving at an amicable solution. Decision-making is a key task of organization top management, managers are expected to choose between two extreme cases, and it depends on the degree of knowledge possessed by those in charge (Shepherd, Williams & Patzelt, 2015).
The first extreme case in decision-making is the one that is deterministic, and the other one that is uncertain. Between the two extreme sides of decisions making process, there are risks, but the main idea is to analyze the degree of certainty depending on the levels of understanding of the business problem. This research paper present decision analysis process using different decision criteria, and different types of scenarios. The research describes certain elements that are important in the analysis before making decisions (Shepherd, Williams & Patzelt, 2015).
In every business decision is related to some aspect of probability, probability is a theoretical idea that helps identify the levels of risks involved in certain business decisions. To determine probability is to identify the degree of risk of the potential outcomes and compare the difference from the benchmark expectation (Albright, Winston & Zappe, 2010). For example, consumers demand forecasts can be determined by random sampling of the target market population to understand their purchasing decision in relation to the cost. The cost of each item is determined by the nearest outcomes that match the cost expectations (Albright, Winston & Zappe, 2010).
Probability means conducting a risk assessment to analyze the expected outcome. Decision-making requires compressive information; probability assessment is done to quantify the information gaps between what is known, and what needs to be known for an optimal decision (Albright, Winston & Zappe, 2010). Probabilistic models are important because of its protection against adverse uncertainty and exploitation from uncertainty. Decision-making can be complex in situations where information is scarce or vague, however, using probabilities, managers can make informed decisions (Albright, Winston & Zappe, 2010).
Suppose that a firm wants to launch a new product in the market, they can administer a pre-launch questionnaire, and if 88 out of the 100 questionnaire respondents said that, they would buy the product this could be translated into a probability statement as follows
p- Product successful = 88 divide by 100 = 0.88. In business, the decision-making process is full of uncertainty, but the more information available, the better the decision. This means trading off values of the specific outcome against the suitable probability (Shirangi & Durlofsky, 2016).
Uncertainty is the state of working with limited knowledge; managers deal with uncertainty and try to reduce risks when making decisions to avoid undesired outcomes (Shirangi & Durlofsky, 2016). Managers need to develop skills o...
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