NARRBEGIN: Number of Fish Tanks Number of Fish Tanks The following data give the number of fish tanks owned for a population of 4 families. $\begin{array} { | l | c c c c | } \hline \text { Family } & \text { A } & \text { B } & \text { C } & \text { D } \\ \hline \text { Number af Fish Tanks Owned } & 2 & 1 & 4 & 3 \\ \hline \end{array}$ NARREND -{Number of Fish Tanks Narrative} A sample of size 2 is drawn at random from the population. Use the formulas $\mu _ { \bar { x } } = \mu$ and $\sigma _ { \bar { x } } = \frac { \sigma } { \sqrt { n } } \sqrt { \frac { N - n } { N - 1 } }$ to calculate the mean and the standard deviation of the sampling distribution of the sample means.

The answer of NARRBEGIN: Number of Fish Tanks Number of Fish...

Exam 9: Sampling Distributions

NARRBEGIN: Heights of Fences Heights of Fences Heights of fences are normally distributed with a mean of 52 inches and a standard deviation of 4 inches.NARREND -{Heights of Fence Narrative} Find the probability that the mean height of 4 randomly selected fences is under 54 inches.

(Short Answer)

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Question 41

Which of the following is true regarding the sampling distribution of the mean for a large sample size? Assume the population distribution is not normal.

(Multiple Choice)

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Question 42

If a simple random sample of 300 observations is taken from a population whose proportion p = 0.6, then the expected value of the sample proportion $\tilde{ p }$ is 0.60.

(True/False)

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Question 43

As n gets larger, the sampling distribution of $\bar { X }$ becomes increasingly bell shaped. This phenomenon is due to the ____________________.

(Short Answer)

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Question 44

A randomly selected value of $\bar { X }$ is likely to be ____________________ to(than) the mean of the population than is a randomly selected value of X.

(Short Answer)

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Question 45

Under certain conditions where n is large enough, you can approximate the distribution using the distribution.

(Short Answer)

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Question 46

The width of the sampling distribution of $\bar { X }$ gets ____________________ as the sample size increases.

(Short Answer)

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Question 47

As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if:

(Multiple Choice)

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Question 48

The amount of bleach a machine pours into bottles has a mean of 50 ounces with a standard deviation of 0.25 ounces. Suppose we take a random sample of 36 bottles filled by this machine. The sampling distribution of the sample mean has a standard error of 0.25 ounces.

(True/False)

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Question 49

NARRBEGIN: DVD Rental Store DVD Rental Store A DVD rental store wants to know what proportion of its customers are under age 21. A simple random sample of 500 customers was taken, and 375 of them were under age 21. Presume that the true population proportion of customers under age 21 is 0.68.NARREND -{DVD Rental Store Narrative} What is the probability that the sample proportion $\tilde{ p }$ is within 0.03 of the true proportion of customers who are under age 21?

(Short Answer)

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Question 50

The Central Limit Theorem states that, if a random sample of size n is drawn from a population, then the sampling distribution of the sample mean $\bar { X }$ :

(Multiple Choice)

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Question 51

NARRBEGIN: Number of Fish Tanks Number of Fish Tanks The following data give the number of fish tanks owned for a population of 4 families. Family A B C D Number af Fish Tanks Owned 2 1 4 3 NARREND -{Number of Fish Tanks Narrative} A sample of size 2 is drawn at random from the population. Use the formulas $\mu _ { \bar { x } } = \mu$ and $\sigma _ { \bar { x } } = \frac { \sigma } { \sqrt { n } } \sqrt { \frac { N - n } { N - 1 } }$ to calculate the mean and the standard deviation of the sampling distribution of the sample means.

(Essay)

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Question 52

Recall the rule of thumb used to indicate when the normal distribution is a good approximation of the sampling distribution for the sample proportion $\tilde{ p }$ . For the combination n = 50, p = 0.05, the rule is satisfied.

(True/False)

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Question 53

If two populations are normally distributed, the sampling distribution of the difference in the sample means, $\bar { X } _ { 1 } - \bar { X } _ { 2 }$ , is:

(Multiple Choice)

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Question 54

The Central Limit Theorem permits us to draw conclusions about a population based on a sample alone, without having any knowledge about the distribution of that population. And this works no matter what the sample size is.

(True/False)

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Question 55

Suppose it is known that 60% of radio listeners at a particular college are smokers. A sample of 500 students from the college is selected at random. Approximate the probability that at least 280 of these students are radio listeners.

(Short Answer)

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Question 56

The probability of success on any trial of a binomial experiment is 20%. Find the probability that the proportion of success in a sample of 400 is: a.less than 18%. b.more than 18%. c.between 18% and 22%.

(Short Answer)

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Question 57

The variance of the sampling distribution of $\bar { X }$ is ____________________ the variance of the population we're sampling from, for any n > 1.

(Short Answer)

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Question 58

NARRBEGIN: Magazines Magazines A local magazine store sells an average of 2,100 magazines per day, with a standard deviation of 500 magazines. Consider a sample of 60 days of operation.NARREND -{Magazines Narrative} Find the expected value and the standard error of the sample mean.

(Essay)

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Question 59

Suppose X has a distribution that is not normal. The Central Limit Theorem is important in this case because:

(Multiple Choice)

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Question 60

Showing 41 - 60 of 154

NARRBEGIN: Heights of Fences Heights of Fences Heights of fences are normally distributed with a mean of 52 inches and a standard deviation of 4 inches.NARREND -{Heights of Fence Narrative} Find the probability that the mean height of 4 randomly selected fences is under 54 inches.

Which of the following is true regarding the sampling distribution of the mean for a large sample size? Assume the population distribution is not normal.

If a simple random sample of 300 observations is taken from a population whose proportion p = 0.6, then the expected value of the sample proportion $\tilde{ p }$ is 0.60.

As n gets larger, the sampling distribution of $\bar { X }$ becomes increasingly bell shaped. This phenomenon is due to the ____________________.

A randomly selected value of $\bar { X }$ is likely to be ____________________ to(than) the mean of the population than is a randomly selected value of X.

Under certain conditions where n is large enough, you can approximate the distribution using the distribution.

The width of the sampling distribution of $\bar { X }$ gets ____________________ as the sample size increases.

As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if:

The amount of bleach a machine pours into bottles has a mean of 50 ounces with a standard deviation of 0.25 ounces. Suppose we take a random sample of 36 bottles filled by this machine. The sampling distribution of the sample mean has a standard error of 0.25 ounces.

The Central Limit Theorem states that, if a random sample of size n is drawn from a population, then the sampling distribution of the sample mean $\bar { X }$ :

Recall the rule of thumb used to indicate when the normal distribution is a good approximation of the sampling distribution for the sample proportion $\tilde{ p }$ . For the combination n = 50, p = 0.05, the rule is satisfied.

If two populations are normally distributed, the sampling distribution of the difference in the sample means, $\bar { X } _ { 1 } - \bar { X } _ { 2 }$ , is:

The Central Limit Theorem permits us to draw conclusions about a population based on a sample alone, without having any knowledge about the distribution of that population. And this works no matter what the sample size is.

Suppose it is known that 60% of radio listeners at a particular college are smokers. A sample of 500 students from the college is selected at random. Approximate the probability that at least 280 of these students are radio listeners.

The probability of success on any trial of a binomial experiment is 20%. Find the probability that the proportion of success in a sample of 400 is: a.less than 18%. b.more than 18%. c.between 18% and 22%.

The variance of the sampling distribution of $\bar { X }$ is ____________________ the variance of the population we're sampling from, for any n > 1.

NARRBEGIN: Magazines Magazines A local magazine store sells an average of 2,100 magazines per day, with a standard deviation of 500 magazines. Consider a sample of 60 days of operation.NARREND -{Magazines Narrative} Find the expected value and the standard error of the sample mean.

Suppose X has a distribution that is not normal. The Central Limit Theorem is important in this case because:

What Is Statistics

Graphical Descriptive Techniques I

Graphical Descriptive Techniques II

Numerical Descriptive Techniques

Data Collection and Sampling

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Introduction to Estimation

Introduction to Hypothesis Testing

Inference About a Population

Inference About Comparing Two Populations

Analysis of Variance

Chi-Squared Tests Optional

Simple Linear Regression and Correlation

Multiple Regression

Filters

Exam 9: Sampling Distributions

NARRBEGIN: Heights of Fences Heights of Fences Heights of fences are normally distributed with a mean of 52 inches and a standard deviation of 4 inches.NARREND -{Heights of Fence Narrative} Find the probability that the mean height of 4 randomly selected fences is under 54 inches.

Which of the following is true regarding the sampling distribution of the mean for a large sample size? Assume the population distribution is not normal.

If a simple random sample of 300 observations is taken from a population whose proportion p = 0.6, then the expected value of the sample proportion p~\tilde{ p }p~​ is 0.60.

As n gets larger, the sampling distribution of Xˉ\bar { X }Xˉ becomes increasingly bell shaped. This phenomenon is due to the ____________________.

A randomly selected value of Xˉ\bar { X }Xˉ is likely to be ____________________ to(than) the mean of the population than is a randomly selected value of X.

Under certain conditions where n is large enough, you can approximate the ____________________ distribution using the ____________________ distribution.

The width of the sampling distribution of Xˉ\bar { X }Xˉ gets ____________________ as the sample size increases.

As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if:

The amount of bleach a machine pours into bottles has a mean of 50 ounces with a standard deviation of 0.25 ounces. Suppose we take a random sample of 36 bottles filled by this machine. The sampling distribution of the sample mean has a standard error of 0.25 ounces.

The Central Limit Theorem states that, if a random sample of size n is drawn from a population, then the sampling distribution of the sample mean Xˉ\bar { X }Xˉ :

Recall the rule of thumb used to indicate when the normal distribution is a good approximation of the sampling distribution for the sample proportion p~\tilde{ p }p~​ . For the combination n = 50, p = 0.05, the rule is satisfied.

If two populations are normally distributed, the sampling distribution of the difference in the sample means, Xˉ1−Xˉ2\bar { X } _ { 1 } - \bar { X } _ { 2 }Xˉ1​−Xˉ2​ , is:

The Central Limit Theorem permits us to draw conclusions about a population based on a sample alone, without having any knowledge about the distribution of that population. And this works no matter what the sample size is.

Suppose it is known that 60% of radio listeners at a particular college are smokers. A sample of 500 students from the college is selected at random. Approximate the probability that at least 280 of these students are radio listeners.

The probability of success on any trial of a binomial experiment is 20%. Find the probability that the proportion of success in a sample of 400 is: a.less than 18%. b.more than 18%. c.between 18% and 22%.

The variance of the sampling distribution of Xˉ\bar { X }Xˉ is ____________________ the variance of the population we're sampling from, for any n > 1.

NARRBEGIN: Magazines Magazines A local magazine store sells an average of 2,100 magazines per day, with a standard deviation of 500 magazines. Consider a sample of 60 days of operation.NARREND -{Magazines Narrative} Find the expected value and the standard error of the sample mean.

Suppose X has a distribution that is not normal. The Central Limit Theorem is important in this case because:

What Is Statistics

Graphical Descriptive Techniques I

Graphical Descriptive Techniques II

Numerical Descriptive Techniques

Data Collection and Sampling

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Introduction to Estimation

Introduction to Hypothesis Testing

Inference About a Population

Inference About Comparing Two Populations

Analysis of Variance

Chi-Squared Tests Optional

Simple Linear Regression and Correlation

Multiple Regression

Filters

If a simple random sample of 300 observations is taken from a population whose proportion p = 0.6, then the expected value of the sample proportion $\tilde{ p }$ is 0.60.

As n gets larger, the sampling distribution of $\bar { X }$ becomes increasingly bell shaped. This phenomenon is due to the ____________________.

A randomly selected value of $\bar { X }$ is likely to be ____________________ to(than) the mean of the population than is a randomly selected value of X.

Under certain conditions where n is large enough, you can approximate the distribution using the distribution.

The width of the sampling distribution of $\bar { X }$ gets ____________________ as the sample size increases.

The Central Limit Theorem states that, if a random sample of size n is drawn from a population, then the sampling distribution of the sample mean $\bar { X }$ :

Recall the rule of thumb used to indicate when the normal distribution is a good approximation of the sampling distribution for the sample proportion $\tilde{ p }$ . For the combination n = 50, p = 0.05, the rule is satisfied.

If two populations are normally distributed, the sampling distribution of the difference in the sample means, $\bar { X } _ { 1 } - \bar { X } _ { 2 }$ , is:

The variance of the sampling distribution of $\bar { X }$ is ____________________ the variance of the population we're sampling from, for any n > 1.