A normal distribution is a type of continuous probability distribution for a real-valued random variable in statistics.
Yes, the large-sample confidence interval will be valid.
<h3>What is meant by normal distribution?</h3>
A normal distribution is a type of continuous probability distribution for a real-valued random variable in statistics.
The normal distribution, also known as the Gaussian distribution, is a symmetric probability distribution about the mean, indicating that data near the mean occur more frequently than data far from the mean.
The confidence interval will be valid regardless of the shape of the population distribution as long as the sample is large enough to satisfy the central limit theorem.
<h3>
What does a large sample confidence interval for a population mean?</h3>
A sample is considered large when n ≥ 30.
By 'valid', it means that the confidence interval procedure has a 95% chance of producing an interval that contains the population parameter.
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Answer:
Step-by-step explanation:
You need to know the formula for the area of a circle , do you?
it's pi*
plug in 1/2 of the diameter , they tell us it's 48 + 6 = 54
54/2 = 27
so
pi*
=2290.2 sq inches
Answer: 8x+12
Distribute the 4. So, 4(2x)+4(3). Then you end up with 8x+12.
Answer:
When sampling from a population, the sample mean will: be closer to the population mean as the sample size increases.
Step-by-step explanation:
The sample mean is not always equal to the population mean but if we increase the number of samples then the mean of the sample would become more and more closer to the population mean.
Usually the population size is very huge that is why we select a random sample from the population, care must be taken to ensure randomized sampling otherwise results would not be accurate. After that we have to make sure that the number of samples are enough for the given population size. The number of samples depends upon the shape of the population. If the population is normal than according to central limit theorem, a less number of samples would be enough to ensure normal distribution of sampling mean, otherwise a greater sample size will be required.
