Understanding Python Coin Flip Streaks: Avoiding Double Probability Errors

Discover how to fix the issue of returning double probabilities in your Python coin flip streak program while learning about streaks of heads and tails in randomized sequences. --- This video is based on the question https://stackoverflow.com/q/70334325/ asked by the user 'Alex' ( https://stackoverflow.com/u/17664837/ ) and on the answer https://stackoverflow.com/a/70334474/ provided by the user 'Andreas' ( https://stackoverflow.com/u/11971785/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions. Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Python - Coin Flip Streaks, returning double as much probability Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/licensing The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/by-sa/4.0/ ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/by-sa/4.0/ ) license. If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com. --- Understanding Python Coin Flip Streaks: Avoiding Double Probability Errors As a budding Python programmer, you may find yourself tackling various exciting projects to hone your skills. One such project involves simulating coin flips to determine how often you encounter a streak of six consecutive heads or tails. However, you might be surprised to discover that your program returns a probability percentage that is far too high—possibly even double what you expected! This can be quite frustrating, especially when you're learning. Let's explore this problem and find out how to resolve it effectively. The Problem: Unexpected Probability Output In your coin flip streak program, you’re likely using a loop to generate 10,000 sequences of 100 coin flips each. The goal is to determine how many times you find a streak of six heads (H) or tails (T) in those sequences. However, if your output suggests a striking probability of around 159% instead of the expected 79-80%, it indicates that something is going wrong in the logic of your code. Why is the Probability Incorrect? The crux of the issue lies in how you're counting occurrences of the sequences. Without proper boundaries around your search patterns, Python is running into instances where it counts streaks multiple times within longer sequences. For example, if your sequence is “T T T T T T T T T T T T”, the count function can identify the pattern in overlapping segments, leading to inflated results. The Solution: Properly Defining Pattern Boundaries To resolve the count inflation issue, you need to set clear boundaries for your search terms. This means specifying unique sequences that don't overlap in ways that would artificially boost your count. Here's how you can adjust your code: Updated Code Snippet [[See Video to Reveal this Text or Code Snippet]] Key Adjustments Explained Replace the previous counting logic with counts that not only consider your desired pattern (“H H H H H H” for heads and “T T T T T T” for tails) but also ensures that these patterns don't overlap. Conclusion: Understanding Coin Flip Streaks By implementing the above changes to your code, you should notice your output percentages return to a more reasonable range of around 79-80%. This exercise teaches us not only about programming with Python but also about the intricacies involved in statistical simulations and the importance of defining clear parameters for data extraction. Keep experimenting with your code, and don't shy away from asking questions in your journey. Each challenge presents a learning opportunity, and understanding the nuances of your programming logic is vital as you move forward with Python. Happy coding!