As a rule of thumb, the sampling distribution of the sample proportion can be approximated by a normal probability distribution whenever the sample size is large.
<h3>What is the Central limit theorem?</h3>
- The Central limit theorem says that the normal probability distribution is used to approximate the sampling distribution of the sample proportions and sample means whenever the sample size is large.
- Approximation of the distribution occurs when the sample size is greater than or equal to 30 and n(1 - p) ≥ 5.
Thus, as a rule of thumb, the sampling distribution of the sample proportions can be approximated by a normal probability distribution when the sample size is large and each element is selected independently from the same population.
Learn more about the central limit theorem here:
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Y=mx +b plug that in , so the 23.95 would be the flat fee then you add 0.32
250 =23.95+0.32 subtract from both sides then divide the answer is 10 miles
n² - 4n = 0
n(n) - n(4) = 0
n(n - 4) = 0
n = 0 or n - 4 = 0
+ 4 + 4
n = 4
Solution Set: {0, 4}
