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Decision Modeling and Risk Analysis with Excel

Decision making using sensitivity analysis, decision tree, utility theory, Bayesian statistics, Monte Carlo simulation.

  1. Topics
  2. Office Productivity
  3. Excel Data Analysis

Decision Modeling and Risk Analysis with Excel

InstructorGancheng Sun
Duration6h 2m
Students12.6K
Rating4.5 (3,557)
Sponsored
Price
$17.99
Coupon
None
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Comidoc Analysis

Decision Modeling and Risk Analysis via Excel

Editorial course preview

What the public course preview actually shows

These 2 complementary views highlight concrete, legible examples from the course presentation.

Preview 1 of 2

This slide outlines the course curriculum, covering Excel basics, decision tree modeling, and Monte Carlo simulation techniques for risk analysis.

Preview 2 of 2

This slide introduces the Feel Good Coffee Inc. case study, detailing that Maria and Robert own a five-store chain in North Carolina used for course scenarios.

Selected from the course's public promotional preview. These images document visible presentation material only; they do not represent the complete paid curriculum.

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Strengths

Applied Case Studies

The curriculum utilizes specific scenarios such as 'Rainbow in a cup', 'Magic' and 'Overbooking' to apply modeling concepts.

Technical Tool Coverage

Instruction covers a wide range of tools including Goal Seek, Solver, Pivot Tables, and the XLRisk add-in for simulations.

Limitations

Rapid Instructional Pacing

Learners have noted that complex theories are sometimes explained too quickly, and software actions can occur at a pace that requires rewinding.

Best suited to

  • Daily Excel users looking for advanced modeling
  • Entrepreneurs managing business uncertainty
  • Learners interested in Monte Carlo simulations

Less suited to

  • Beginners requiring slow-saced theoretical explanations
  • Students seeking deep statistical theory before practical application

Comidoc Score

6.4/10

Worth considering
Advanced focus

Comidoc verdict

The learning path moves from Excel essentials into specialized decision analysis, including Bayes' Theorem and Monte Carlo simulations. The curriculum is highly practical, utilizing case studies and templates to demonstrate how uncertainty can be modeled within spreadsheets.

However, the instructional delivery presents a significant trade-off in pacing. While effective for those already comfortable with software operations, the rapid explanation of complex statistical concepts may make it difficult for others to retain information without frequent review. Some learners have noted that assignments lack detailed video walkthroughs for their solutions.

This course is best suited for experienced Excel users or professionals who need to apply decision modeling quickly and can manage a fast-paced instructional style.

Score breakdown

Curriculum depth
6.5

The curriculum covers diverse topics like decision trees and simulations, though some signals suggest a need for more depth in theory before practical application.

Applied learning
8.0

The course includes multiple case studies and practical exercises that apply modeling concepts to real-world scenarios.

Clarity & experience
5.0

Instructional signals are mixed; while some find the content clear, others report that the rapid pacing and single-pass explanations make it difficult to follow.

Currency & reliability
5.0

The available evidence does not establish enough about current reliability to move this dimension away from neutral.

Audience fit
6.5

Theory-to-Practice Gap

Some signals suggest that the Monte Carlo simulation portion would benefit from more extensive theoretical groundwork prior to exercises.

The curriculum aligns well with the stated goals of analyzing uncertainty using Excel tools.

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  • Uncertainty Analysis61
  • Monte Carlo Simulation38
  • Bayesian Statistics26
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  • Advanced Microsoft Excel46
  • Power Pivot for Excel94
  • Excel VBA Programming322