Question

Which of the following statements concerning sampling is false? (1) The Central Limit Theorem is very important for statistic

0 0
Add a comment Improve this question Transcribed image text
Answer #1

and The Central limit theorem states theorem states that if you have a population with mean u standard deviation and take suf

Add a comment
Know the answer?
Add Answer to:
Which of the following statements concerning sampling is false? (1) The Central Limit Theorem is very...
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for? Ask your own homework help question. Our experts will answer your question WITHIN MINUTES for Free.
Similar Homework Help Questions
  • Which of the following statements concerning sampling is false? (1) The Central Limit Theorem is very...

    Which of the following statements concerning sampling is false? (1) The Central Limit Theorem is very important for statistical inference. (2) The standard error of an estimator is the standard deviation of a statistic. (3) Regardless of the sample size n, if the population distribution is normal then the sampling distribution of ī will be exactly normal. (4) If the sampled population is uniform then the sampling distribution of ī is also approximately uniform.

  • 7 SAMPLING DISTRIBUTIONS (31) Sampling distributions describe the behaviour of population parameters in repeated sam pling...

    7 SAMPLING DISTRIBUTIONS (31) Sampling distributions describe the behaviour of population parameters in repeated sam pling (1) True. (2) False (32) Which of the following statements concerning sampling is false? (1) The Central Limit Theorem is very important for statistical inference. (2) The standard error of an estimator is the standard deviation of a statistic. (3) Regardless of the sample size n, if the population distribution is normal then the sampling distribution of will be exactly normal. (4) If the...

  • The Central Limit Theorem is important in statistics because _. A for a large n, it...

    The Central Limit Theorem is important in statistics because _. A for a large n, it says the population is approximately normal B for any population, it says the sampling distribution of the sample mean is approximately normal, regardless of the sample size C for a large n, it says the sampling distribution of the sample mean is approximately normal, regardless of the population D for any size sample, it says the sampling distribution of the sample mean is approximately...

  • If I has a normal distribution, then 7 always has a normal distribution. True False Under...

    If I has a normal distribution, then 7 always has a normal distribution. True False Under what condition does the sample mean ī not have a normal distribution? Population is not normal but the sample size n > 30. Population is not normal and sample size n <30. Population is normal. The Central Limit Theorem for a sample mean (@) is very important in Statistics because it states that for large sample sizes, the population distribution is approximately normal. for...

  • In the notes there is a Central Limit Theorem example in which a sampling distribution of means i...

    R Programming codes for the above questions? In the notes there is a Central Limit Theorem example in which a sampling distribution of means is created using a for loop, and then this distribution is plotted. This distribution should look approximately like a normal distribution. However, not all statistics have normal sampling distributions. For this problem, you'll create a sampling distribution of standard deviations rather than means. 3. Using a for loop, draw 10,000 samples of size n-30 from a...

  • The Central Limit Theorem tells us that the sampling distribution of the sample mean can be...

    The Central Limit Theorem tells us that the sampling distribution of the sample mean can be approximated with a normal distribution for “large”n as n gets bigger, the sample data becomes more like the normal distribution if the data comes from an (approximately) normally distributed population, then the sample mean will also be (approximately) normally distributed the minimum variance unbiased estimator is the "best" estimator for a parameter

  • Which of the following conditions implies that the Central Limit Theorem can be applied? A. The...

    Which of the following conditions implies that the Central Limit Theorem can be applied? A. The population is approximately normally distributed B. The sample is approximately normally distributed C. σ is not known D. μ is not known E. μ is known Which of the following conditions implies that the Central Limit Theorem can be applied? A. The sample is approximately normally distributed B. The sample size is at least 30 C. μ is not known D. σ is not...

  • Question (1) According to the Central Limit theorem, what is the standard deviation of the sampling...

    Question (1) According to the Central Limit theorem, what is the standard deviation of the sampling distribution of the sample mean? (02 marks) ► The standard deviation of the population The standard deviation of the sample ► The standard deviation of the population divided by the square root of the sample size. The standard deviation of the sample divided by the square root of the sample size.

  • Please explain, I dont really understand 7. True or False? The central limit theorem tells us...

    Please explain, I dont really understand 7. True or False? The central limit theorem tells us that as the sample size increases, the sampling distribution of the sample mean approaches an approximately normal distribution REGARDLESS OF the original population data distribution. 8. True or False? Student t-distribution, regardless its degree of freedom, has heavier tails than the standard normal distribution. 9. In a hypothesis test we always assume the hypothesis unless we have sufficient evidence for the hypothesis 10. In...

  • The central limit theorem says that when a simple random sample of size n is drawn...

    The central limit theorem says that when a simple random sample of size n is drawn from any population with mean μ and standard deviation σ, then when n is sufficiently large the distribution of the sample mean is approximately Normal. the standard deviation of the sample mean is σ2nσ2n. the distribution of the sample mean is exactly Normal. the distribution of the population is approximately Normal.

ADVERTISEMENT
Free Homework Help App
Download From Google Play
Scan Your Homework
to Get Instant Free Answers
Need Online Homework Help?
Ask a Question
Get Answers For Free
Most questions answered within 3 hours.
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT