Can you explain the central limit theorem using the example of a group of coin flip trials (our population) where each trial has the same number of tosses (our sample size), and we are looking at the number of heads we get per trial, but increasing our sample size produces a normal distribution (because increasing the number of coin flips per trial decreases the likelihood that we will get extreme results on a trial--such as no heads or all heads)?
Can you explain the central limit theorem using the example of a group of coin flip trials (our population) where each trial has the same number of tosses (our sample size), and we are looking at the number of heads we get per trial, but increasing our sample size produces a normal distribution (because increasing the number of coin flips per trial decreases the likelihood that we will get extreme results on a trial--such as no heads or all heads)?
College Algebra
7th Edition
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter9: Counting And Probability
Section9.3: Binomial Probability
Problem 2E: If a binomial experiment has probability p success, then the probability of failure is...
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Can you explain the central limit theorem using the example of a group of coin flip trials (our population) where each trial has the same number of tosses (our sample size), and we are looking at the number of heads we get per trial, but increasing our sample size produces a normal distribution (because increasing the number of coin flips per trial decreases the likelihood that we will get extreme results on a trial--such as no heads or all heads)?
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