# Probability Theory  for Data Analysis  and Decision-Making

Probabilistic decision models are useful, but to make full use of their potential, you have to be trained in probability. As the bedrock of statistical analysis, this course is designed to provide you with a foundational understanding of probability theory's principles, applications, and real-world relevance. Whether you're a data analyst seeking to enhance your quantitative skills or a decision-maker looking to make more calculated choices, our course enables professionals to assess risk, forecast outcomes, and optimize strategies with precision.

Syllabus

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## Markovian Decision Models

ArrowHead’s Decision Analysis training course will provide you with a comprehensive grasp of essential concepts drawn from the famed Stanford Decision Analysis course that Dr. Nesbitt has been teaching. This session gives you a practical understanding of the key concepts designed for pencil and paper calculation by covering fundamental topics like alternatives, probabilities, decision trees, influence diagrams, Bayesian networks, and values and risk attitude.

In this module, you'll delve into the art of harnessing computer-generated samples to infer probability. We will explore Monte Carlo integration, generating densities from shapes, sampling from univariate and multivariate densities, and deriving distributions from samples. Additionally, we'll navigate the challenges and pitfalls associated with applying simulation techniques to economic models.

In this module, we'll explore the intricacies of obtaining probability distributions for different variables, such as price. We'll cover various techniques, including the probability wheel, data-driven probability assessment using the Nesbitt Bayesian Linear Regression method, the Keelin meta-log method, and the discretization of continuous probabilities to create decision trees.

Dr. Nesbitt's definitive text and course on Bayesian regression serve as the foundation for this module. Here, you'll learn to leverage prior probability estimates and data to construct sophisticated, valid probability distributions. We'll explore "zero information" priors and harness probability distributions for accurate forecasting. Patterned after Dr. Nesbitt's renowned Stanford course, this world-class statistical analysis method and course that supersedes classical linear regression, equipping you with easily programmable methods for both large and small data sets.

You will learn to harness the power of Markov and semi-Markov decision processes, which excel at representing dynamic probabilities and outcomes over time, enabling you to adapt and mitigate risks effectively. We cover both transient and recurrent processes, including decision trees and long-term state transitions, enabling you to analyze scenarios such as preventive maintenance, rehabilitation, and replacement.

## Course Features

Probability theory is a powerful tool that allows you to quantify uncertainty and assess the likelihood of various outcomes in a wide range of scenarios. Join us on this educational journey, and empower yourself to harness the power of probability theory for insightful analysis and strategic decision-making.

Durration

### 1 Week Course

Split to accommodate your schedule & availability

Composition

### 2 Modules

Designed to focus on your most pressing needs

In-Class

### 30 Hours of Lecture Time

Can't join? Live sessions are recorded so you can watch or re-watch on your time.

At Home

### 4 Hours Independent Study

Retain information more thoroughly through guided independent study.

Materials

### Course Material Provided

Follow along with our comprehensive course material package—yours to keep and refer back to

Recognition

### Certificate upon Completion

Demonstrable proof of your grasp of our various training programs

## “This course was a game-changer for our decision-making. Now, we don't just guess; we calculate, predict, and optimize with more confidence. Our company's data analysis has leveled up, and we're seeing tangible improvements in our strategies and outcomes."”

Senior Strategic Planner

### Analise Gomes

Major Oil & Gas Company

01

What is Probability Theory?

Probability theory is a branch of mathematics that helps us understand and predict how likely different events are to happen. It provides a way to measure & describe uncertainty. Simply put, it's all about figuring out the chances of something occurring or not occurring, and is used in fields like science, statistics, and finance to make informed decisions when outcomes are uncertain.

02

How do I turn theory into practice?

When faced with a decision, a foundational understanding of probability theory can help you better consider the probabilities associated with each choice's potential outcomes. This helps you make more informed choices by weighing the risks and benefits, and guides you toward decisions that have a higher chance of success. Essentially, probability theory provides a way to quantify uncertainty and use that information to make better decisions in various aspects of business.

03

Do I have the credentials to grasp these concepts?

Absolutely! we make complex theory into simple, actionable, easy-to-digest concepts that your team can leverage daily. That's right, there are no prerequisites, just clean, actionable concepts.

consulting

Dr. Dale Nesbitt

With over four decades of experience in economic modeling, probability modeling, decision analysis, and research, as well as an educator, Dr. Dale Nesbitt has left an indelible mark on each. He has led ArrowHead (and his predecessor companies) to numerous successful economic modeling, decision analysis, probabilistic modeling, and ethics engagements, creating billions of dollars worth of value. He has been teaching as an Adjunct Lecturer at Stanford (Management Science and Engineering), and he now brings his expertise directly to you and your team.

Dr. Dale Nesbitt