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Understanding how to estimate probability is essential in various real-world situations, enabling us to make informed predictions based on experimental results. In today's lesson, we will explore the concepts of theoretical versus experimental probability, emphasizing how the law of large numbers informs our estimations. Through practical examples, like rolling dice or flipping coins, we can apply these principles to anticipate outcomes in different scenarios. Join us as we review quiz results, note key concepts in probability estimation, and tackle exercises to solidify our understanding.
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How can estimating probability be important in real world situations? Question of the day
Agenda • Go over quiz • Notes on estimation probability • Lesson 8 exercise • Exit ticket
Theoretical vs. Experimental probability while estimating Notes
Using estimation in probability • After experimenting with one group, we can use that group to estimate what the outcome would be in another group • If we roll a die ten times and it lands on a two twice. What can we estimate the number of twos rolled if we roll the die 20 times? • P(2)= • =
Using estimation between theoretical and experimental • If we know the theoretical probability, we can use that to estimate what would happen in an experiment • If the theoretical probability of flipping a coin and it landing on heads is • P(head)= • How many heads would you expect to land on if you, experimentally, flipped the coin 30 times • =
Ideas to remember • Law of large numbers • Experimental probability is the same as relative frequency
Assignment • Lesson 8 exercise#1-9
Exit ticket • If is rains about 1 day a week, then how many days should it rain in a month. • *assume there are four weeks in a month.
