Great Courses Plus – What Are The Chances – Probability Made Clear

What You’ll Discover in Great Courses Plus What Are The Chances Probability Made Clear

These are just a few of the many possibilities that you’ll explore when investigating probability as a reasoning instrument:
When was the most recent common ancestor all humankind born?
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Great Courses Plus – What Are The Chances – Probability Made Clear

What Are The Chances? Probability Made Clear helps You understand the random factors that lurk behind almost everything—from the chance combinations of genes that produced you Because of the high likelihood that a bus stop’s waiting time will be longer than average, if they have a random schedule, it is likely that there will be a longer wait.

 In 12 stimulating half-Hour lectures will cover the basic concepts and interesting applications of probability.

 High Probability This Course is a Must-See

 Professor Michael Starbird knows how to make numbers live beyond non-Mathematicians are known for picking interesting, useful, and fun examples. Here are some examples that you can use in your exploration of probability as an reasoning tool.

• When was the last common ancestor of all humankind? Based on probabilistic methods and the observed mutation rate in human genetic material, scientists have traced back our lineage to a female ancestral who lived approximately 150,000 years before us.
• How much should you spend on a stock option Options trading was considered gambling until 1970 when Fischer Black and Myron Schles created a way to quantify these risks and create a rational pricing model.
• What What do you do when third down is given with long yardage? If you have many yards to go, the obvious play is to pass. The other team will know that. Probability Game theory and game theory will help you to decide when to run with a ball to keep your opponent guessing.

What What You’ll Learn

 The Course begins literally with a roll on the dice. Professor Starbird shows that games of chance are a great way to illustrate basic principles of probability. He also explains the importance of counting all possible outcomes for any random event. Lecture 2 examines the nature and effects of randomness. It is well-recognized by monkeys hitting typewriter keys randomly, creating randomness. Hamlet. Lecture 3 will explore the concept expected value. This is the average net loss/gain from performing experiments or playing a game several times. Then, in Lecture 4, you will explore the simple but mathematically sound idea of random walk. While it might seem like a way to get nowhere, it has important applications across many fields.

 This introduction will provide a foundation for understanding the concepts of probability and allow you to explore the many applications. Lectures 5 & 6 demonstrate that probability and randomness are key components of scientific descriptions of the world of physics and biology. Lecture 7 examines finance, including probabilistic models of stock- and option behavior. Lecture 8 looks at unusual applications, such as game theory, which studies strategic decision making.-Making in games, wars and business. Next, Lecture 9 will discuss two famous probability puzzles that are guaranteed to make a stir: The birthday problem and The Let’s make a deal® Monty Hall question.

 Finally, Lectures 10–12 cover increasingly sophisticated and surprising results of probabilistic reasoning associated with Bayes theorem. The Course ends with probability paradoxes.

 Take the Weather Forecasting Challenge

 Weather reports are a familiar experience of probability. They include predictions like “There is a 30 percent chance of rain tomorrow.” What does this mean? What Do You think? Pick one:

• (a) Rain will be 30 percent of the time.
• (b) Rain is possible at a certain point in the forecast area.
• (c) The forecast area is at 30 percent risk of rain during the day.
• (d) Rain will fall on 30% of the area forecast, but not 70%.
• (e), None of the above.

 In Lecture 5, Dr. Starbird puts this particular forecast under the microscope to demonstrate that probabilistic statements have very precise meanings that can easily be misinterpreted—or misstated. He explains the reason that the answer is (e), and not one of other options. He also explains the reason why the official National Weather Service definition is incorrect.

 He even believes that in five years, the official definition will be changed because someone from the National Weather Service is going to hear it!

 People Play Games

 The At the dice table, formal probability studies were initiated. Gambling provides many examples of how probability and chance work, including:

• Gambler’s ruin: A random walk is a sequence of steps in which the direction of each step is taken at random. In gambling, the phenomenon assures that a bettor who repeatedly plays the same game with even odds will eventually—and invariably—go broke.
• St. Petersburg paradox: A famous problem in probability involves a hypothetical game supposedly played at a casino in St. Petersburg. Although the game may seem simple and profitable to the gambler, its expected value is incalculable! But it is not something that a reasonable person would pay to play. Why would you?
• Gambler’s addiction: Randomness plays a valuable role in reinforcing animal behavior. Changes in reinforcement can lead to behavior retention that lasts for long time and even when rewards are not available. This observation can be applied to humans and may explain compulsive gambling.

 Probability The Rescue

 Thomas Bayes, a mathematician who was also ordained by the Presbyterian Church, in 18th-century developed a method for interpreting probability. He used degrees of belief to interpret it. As more information becomes available, probability calculations will change to reflect the new information. The Bayesian views reflect the fact that our knowledge is constantly being updated by evidence.

 The A world of fluctuating probability, constantly adjusted as new evidence is discovered, captures how the world works in areas like medicine. Here, a physician makes a preliminary diagnose based on symptoms, probabilities and orders tests. Then, the doctor refines the diagnosis based the test results and new probabilities.

 This is how you work as a juror. The defendant is likely to be guilty or innocent at the beginning. As more evidence is presented, you adjust each verdict’s relative probabilities. Although you may not be able to do a formal calculation your informal process is Bayesian.

 Randomness surrounds us all. “Many or most parts of our lives involve situations where we don’t know what’s going to happen,”Professor Starbird says: Probability It comes in handy to explain what to expect from randomness. It’s a powerful tool to dispel illusions and uncertainty, helping us to understand the true odds of winning the game of life.

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