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.
To learn more about normal distribution, refer to:
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I think the correct answer would be true. The quantity represented by theta is a function of time. This is because the rate of change of angular speed is constant which means the angular distance is changing with time. Hope this answers the question. Have a nice day.
Where's the graph? If you can give me the graph then I'd be able to answer for you.
