Answer:
he correct answer is Jack should see the experimental probability of getting tails decrease and come closer to 0.500 due to the Law of Large Numbers. The law of large numbers indicates that if an event of probability p is observed repeatedly during independent repetitions, the ratio of the observed frequency of that event to the total number of repetitions approaches p as the number of repetitions becomes arbitrarily large.Step-by-step explanation:
Jack should see the experimental probability of getting tails decrease and come closer to 0.500 due to the Law of Large Numbers.(Option B).
Weak law of large number says that the sample mean converges in probability to the expected mean as the sample size grows more and more.
Symbolically, we write it as:
[tex]\overline{X}_n \xrightarrow {P} E(X) \: \: \: \rm when \: \: \: n \rightarrow \infty[/tex]
where n is the sample size.
In this case,
The samples is made up by the result of 'n' times coin flips, so sample is those 'n' experiments' results.
The probability of getting a tail is actually meant to be experimental probability of getting a tail.
Let X represents the number of times tail comes in n times coin flip.
Then experimental probability is:
X/n
Now, as n increases, X converges to E(X), and we know that E(X)/n= 0.5 (the probability of getting a tail in a fair coin is 0.5), therefore, as n increases, the experimental probability of getting a tail converges to 0.5.
Thus, Jack should see the experimental probability of getting tails decrease and come closer to 0.500 due to the Law of Large Numbers.(Option B).
Learn more about experimental probability here:
https://brainly.com/question/2547434
