TRUE OR FALSE The sampling distribution of the sample mean is approximately normal as the sample size n increases.
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Q: Sample size depends on population size? True False
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A: List of formulae : Mean of sampling distribution of sample proportion ( p^ ) : μp^ = p Standard…
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Q: True or False: If the population distribution given is normally distributed, then the sampling…
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Q: hat ways (if any) does changing the sample size influence sampling error and standard error
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Q: rationale for using n – 1 to compute the sample variance
A: we divide by 'n' to get the population variance.
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Q: (a) Find the standard error of the mean for each sampling situation (assuming a normal population).…
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Q: e or fals
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TRUE OR FALSE
The sampling distribution of the sample
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- A population of values has a normal distribution with M=153.9 and O=82.9 You intend to draw a random sample of size n=115. A). Find P86, which is the score separating the bottom 86% scores from the top 14% scores. P86 (for single values) =__________ B). Find P86, which is the mean separating the bottom 86% means from the top 14% means. P86 (for sample means) =_________True or false?Can a normal approximation be used for a sampling distribution of sample means from a population with u = 55 and o = 10, when n = 4? Answer E Tables E Keypad Keyboard Shortcuts O Yes, because the mean is greater than 30. O Yes, because the sample size is less than 30. O No, because the sample size is less than 30. O No, because the standard deviation is too small.
- Find the mean and variance for the binomial distribution, Sample size (n) = 22 and P=0.28A produce packing company prepares crates of apples for shipping to supermarkets. Suppose that the weight of a randomly selected crate is known to have a mean of 20 kg and a standard deviation of 1.2 kg. (a) If 100 crates prepared by this company are randomly selected, describe the approximate distribution of the mean weight of the sample. Justify your answer. (b) Suppose the same 100 crates are placed into a truck for shipment. On the way to its destination, the truck must stop at a weighing station. If the combined weight of the cargo (not counting the weight of the truck) is more than 2015 kg, the truck must undergo further inspection. What is the approximate probability that this will occur?What happens to the t-distribution as the sample size increases?
- Distribution of sample means e.SCAN Suppose a simple random sample of size n =75 is obtained from a population whose size is N= 10,000 and whose population proportion with a specified characteristic is p= 0.4. Click here to view the standard normal distribution table (page 1). Click here to view the standard normal distribution table (page 2). .... (a) Describe the sampling distribution of p. Choose the phrase that best describes the shape of the sampling distribution below. O A. Not normal becausens0.05N and np(1 -p) 2 10. B. Approximately normal because ns0.05N and np(1- p)2 10. C. Not normal because ns0.05N and np(1-p)< 10. AC O D. Approximately normal because n<0.05N and np(1 -p)<10. OFF Determine the mean of the sampling distribution of p. = (Round to one decimal place as needed.) %3D Clear all View an example Get more help - Help me solve this G Search or type URL esc 23 8 1 2 3 Q W E R %24 56In an analysis of variance where the total sample size for the experiment is nT and the number of populations is k, the mean square due to error is a. SSE/(nT-k) b. SSTR/(nT-k) c. SSE/(k-1) d. SSTR/k
- True? Determine whether the following statement is true: When random samples of 50 men and 50 women are obtained and we want to test the claim that men and women have different mean annual incomes, there is no need to confirm that the samples are from populations with normal distributions.Study groups are equivalent means that they are exactly the same number of male and female participants in each group statistically the same because sampling error is eliminated experimentally the same statistically equal, with small differences between groups due to sampling errorThe distribution of average hours worked per week for random samples of 1000 workers in the U.S. has a mean of 40 and a standard error of 0.04 The distribution in this scenario is a: sampling distribution sample distribution population distribution
