1. A.Explain why the spread (variance) of a sampling distribution for estimating a mean would be...
1. A.Explain why the spread (variance) of a sampling distribution for estimating a mean would be smaller than the spread (variance) of the whole population.
B.Discuss what happens to the shape AND spread of a sampling distribution as sample size (n) is increased.
C.Explain why it is essential that the sampling distribution be normally distributed (or t-distributed) in order to do the statistical inference procedures.
Homework Answers
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1. A.Explain why the spread (variance) of a sampling
distribution for estimating a mean would be...
Which of the following statements about the sampling distribution of the sample mean, x-bar, is not...
Which of the following statements about the sampling distribution of the sample mean, x-bar, is not true? The distribution is normal regardless of the shape of the population distribution, as long as the sample size, n, is large enough. The distribution is normal regardless of the sample size, as long as the population distribution is normal. The distribution's mean is the same as the population mean. The distribution's standard deviation is smaller than the population standard deviation. All of the...
For the following, circle true or false and if false, explain why. A) The sampling distribution...
For the following, circle true or false and if false, explain why. A) The sampling distribution of sample means is normally distributed when the population has any distribution and the sample size is less than or equal to 30. TRUE or FALSE B) The sampling distribution of sample means is normally distributed when the population is normally distributed and the sample is any size. TRUE or FALSE
Which of the following statements about the sampling distribution of the sample mean, x-bar, is not...
Which of the following statements about the sampling distribution of the sample mean, x-bar, is not true? The distribution is normal regardless of the shape of the population distribution, as long as the sample size,n, is large enough. The distribution is normal regardless of the sample size, as long as the population distribution is normal. The distribution's mean is the same as the population mean. The distribution's standard deviation is smaller than the population standard deviation. All of the above...
Which of the following is true about the sampling distribution of means? Shape of the sampling...
Which of the following is true about the sampling distribution of means? Shape of the sampling distribution of means is always the same shape as the population distribution, no matter what the sample size is. Sampling distribution of the mean is always right skewed since means cannot be smaller than 0. Sampling distributions of means are always nearly normal. Sampling distributions of means get closer to normality as the sample size increases.
When estimating a population mean by a sample mean, the margin of error does NOT depend...
When estimating a population mean by a sample mean, the margin of error does NOT depend on ______. A) The confidence level B) The sample mean C) The sample size D) The population standard deviation What is the sampling distribution of a statistic? A) The distribution of observations of the statistic for all possible sizes of samples from a population B) The distribution of all possible observations of the statistic for samples of a given size from a population C)...
Solocting a distribution for inforences on the population mean Suppose that we want to estimate the number of holdi...
Solocting a distribution for inforences on the population mean Suppose that we want to estimate the number of holding penalties assessed during a college football game. The sample of games we pick has a mean of 3.4 penalties per game and a standard deviation of 0.7 penalties per game. For each of the following sampling scenarios, determine which test statistic is appropriate to use when making inference statements about the population mean. (In the table, Z refers to a variable...
1. Select all true statements about sample mean and sample median. A) When the population distribution...
1. Select all true statements about sample mean and sample median. A) When the population distribution is skewed, sample mean is biased but sample median is an unbiased estimator of population mean. B) When the population distribution is symmetric, both mean and sample median are unbiased estimators of population mean. C) Sampling distribution of sample mean has a smaller standard error than sample median when population distribution is normal. D) Both mean and median are unbiased estimators of population mean...
You would like to estimate the mean price of milk (per gallon) in your city. You...
You would like to estimate the mean price of milk (per gallon) in your city. You select a random sample of prices from different stores. The sample has a mean of 3.75 dollars and a standard deviation of 0.21 dollars. For each of the following sampling scenarios, determine which test statistic is appropriate to use when making inference statements about the population mean. (In the table, Z refers to a variable having a standard normal distribution, and t refers to...
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
Question 1 1 pts The sampling distribution of the sample mean refers to d the distribution...
Question 1 1 pts The sampling distribution of the sample mean refers to d the distribution of the different possible values of the sample mean O the distribution of the various sample sizes O the distribution of the values of the objects/individuals in the population O the distribution of the data values in a given sample O none of the listed Question 2 1 pts The Central Limit Theorem states that O if the sample size is large, then the...
Which of the following statements about the sampling distribution of the sample mean, x-bar, is not true? The distribution is normal regardless of the shape of the population distribution, as long as the sample size, n, is large enough. The distribution is normal regardless of the sample size, as long as the population distribution is normal. The distribution's mean is the same as the population mean. The distribution's standard deviation is smaller than the population standard deviation. All of the...
Solocting a distribution for inforences on the population mean Suppose that we want to estimate the number of holding penalties assessed during a college football game. The sample of games we pick has a mean of 3.4 penalties per game and a standard deviation of 0.7 penalties per game. For each of the following sampling scenarios, determine which test statistic is appropriate to use when making inference statements about the population mean. (In the table, Z refers to a variable...
You would like to estimate the mean price of milk (per gallon) in your city. You select a random sample of prices from different stores. The sample has a mean of 3.75 dollars and a standard deviation of 0.21 dollars. For each of the following sampling scenarios, determine which test statistic is appropriate to use when making inference statements about the population mean. (In the table, Z refers to a variable having a standard normal distribution, and t refers to...
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
Question 1 1 pts The sampling distribution of the sample mean refers to d the distribution of the different possible values of the sample mean O the distribution of the various sample sizes O the distribution of the values of the objects/individuals in the population O the distribution of the data values in a given sample O none of the listed Question 2 1 pts The Central Limit Theorem states that O if the sample size is large, then the...
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