If something has a 1% chance of success, trying it 100 times does NOT guarantee you’ll succeed. This is one of the most common misunderstandings in probability. A 1% success rate means each attempt has a probability of 0.01. But probability doesn’t “accumulate” in a simple linear way where 1% × 100 = 100%. Each trial is independent (assuming conditions don’t change). The correct way to think about this is: * Probability of failure in one trial = 0.99 * Probability of failing 100 times in a row = 0.99^100 ≈ 0.366 * So, probability of at least one success = 1 − 0.99^100 ≈ 0.634 That’s about a 63.4% chance of success after 100 tries — not 100%. Even after 100 attempts, there’s still a 36.6% chance you fail every single time. This is why: * Rare events stay rare even with repetition * “I’m due for a win” is not mathematically valid * Systems that rely on small probabilities require large sample sizes to stabilize outcomes In real-world terms: startups, experiments, drug trials, ma...