The expected value of the sampling distribution of the sample mean $\bar { X }$ equals the population mean $\mu$: $\begin{array}{|l|l|} \hline A&\text { when the population is normally distributed.}\\ \hline B&\text {when the population is symmetric. }\\ \hline C&\text {when the population size \( N>30 $. }\\ \hline D&\text { for all populations.}\\ \hline \end{array}\)

The answer of The expected value of the sampling distribution...

If a random sample of size n is drawn from a normal population, then the sampling distribution of the sample mean $\bar { X }$ will be: $\begin{array}{|l|l|} \hline A&\text { normal for all values of \( n $.}\\ \hline B&\text {normal only for $ n>30 $. }\\ \hline C&\text { approximately normal for all values of $ n $.}\\ \hline D&\text {approximately normal only for $ n>30 $. }\\ \hline \end{array}\)

The answer of If a random sample of size n...

Random samples of size 64 are taken from an infinite population whose mean is 160 and standard deviation is 32. The mean and standard error of the sample mean, respectively, are: $\begin{array}{|l|l|} \hline \text { A. } & 160 \text { and } 32 . \\ \hline \text { B. } & 64 \text { and } 32 . \\ \hline \text { C. } & 160 \text { and } 4 . \\ \hline \text { D. } & 20 \text { and } 4 . \\ \hline \end{array}$

The answer of Random samples of size 64 are taken...

The standard deviation of the sampling distribution of the sample mean is also called the: $\begin{array}{|l|l|} \hline A&\text { central limit theorem.}\\ \hline B&\text { standard error of the mean.}\\ \hline C&\text { finite population correction factor.}\\ \hline D&\text {population standard deviation. }\\ \hline \end{array}$

The answer of The standard deviation of the sampling distribution...

The following table gives the number of pets owned for a population of four families. \[\begin{array} { | l | c | c | c | c | } \hline \text { Family } & \text { A } & \text { B } & \text { C } & \text { D } \\ \hline \text { Number of pets owned } & 2 & 1 & 4 & 3 \\ \hline \end{array}\] Find the sampling distribution of $\bar { X }$ .

The answer of The following table gives the number of...

As a general rule in computing the standard error of the sample mean, the finite population correction factor is used only if the: $\begin{array}{|l|l|} \hline A&\text { sample size is smaller than \( 10 \% $ of the population size. }\\ \hline B&\text { population size is smaller than $ 10 \% $ of the sample size.}\\ \hline C&\text { sample size is greater than $ 1 \% $ of the population size. }\\ \hline D&\text {population size is greater than $ 1 \% $ of the sample size. }\\ \hline \end{array}\)

The answer of As a general rule in computing the...

Exam 10: Sampling Distributions

The expected value of the sampling distribution of the sample mean $\bar { X }$ equals the population mean $\mu$ : A when the population is normally distributed. B when the population is symmetric. C when the population size N>30 . D for all populations.

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Question 41

The sampling distribution of the sample proportion has mean p and variance pq/n.

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Question 42

If the daily demand for boxes of mineral water at a supermarket is normally distributed with a mean of 47.6 boxes and a standard deviation of 5.8 boxes, what is the probability that the average demand for a sample of 10 supermarkets will be less than 50 boxes in a given day?

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Question 43

If a random sample of size n is drawn from a normal population, then the sampling distribution of the sample mean $\bar { X }$ will be: A normal for all values of n . B normal only for n>30 . C approximately normal for all values of n . D approximately normal only for n>30 .

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Question 44

Suppose that the time needed to complete a final exam is normally distributed with a mean of 85 minutes and a standard deviation of 18 minutes. a. What is the probability that the total time taken by a group of 100 students will not exceed 8200 minutes? b. What assumption did you have to make in your computations in part (a)?

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Question 45

Random samples of size 64 are taken from an infinite population whose mean is 160 and standard deviation is 32. The mean and standard error of the sample mean, respectively, are: A. 160 and 32. B. 64 and 32. C. 160 and 4. D. 20 and 4.

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Question 46

The heights of women in Australia are normally distributed, with a mean of 165 centimetres and a standard deviation of 10 centimetres. If the population of women's heights were not normally distributed, which, if any, of the following questions could you answer? A) What is the probability that a randomly selected woman is taller than 160 cm? B) A random sample of five women is selected. What is the probability that the sample mean is greater than 160 cm? C) What is the probability that the mean height of a random sample of 75 women is greater than 160 cm?

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Question 47

The standard deviation of the sampling distribution of the sample mean is also called the: A central limit theorem. B standard error of the mean. C finite population correction factor. D population standard deviation.

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Question 48

If all possible samples of size n are drawn from an infinite population with a mean of 15 and a standard deviation of 5, then the standard error of the sample mean equals 1.0 only for samples of size: A. 5. B. 15. C. 25. D. 75.

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Question 49

Consider an infinite population with a mean of 100 and a standard deviation of 20. A random sample of size 50 is taken from this population. The standard deviation of the sample mean equals 3.2.

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Question 50

An infinite population has a mean of 100 and a standard deviation of 20. Suppose that the population is not normally distributed. What does the central limit theorem say about the sampling distribution of the mean if samples of size 64 are drawn at random from this population?

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Question 51

The following table gives the number of pets owned for a population of four families. Family A B C D Number of pets owned 2 1 4 3 Find the sampling distribution of $\bar { X }$ .

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Question 52

In order to estimate the mean salary for a population of 500 employees, the managing director of a certain company selected at random a sample of 40 employees. a. Would you use the finite population correction factor in calculating the standard error of the sample mean? Explain. b. If the population standard deviation is $800, compute the standard error both with and without using the finite population correction factor. c. What is the probability that the sample mean salary of the employees will be within ±$200 of the population mean salary?

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Question 53

If a random variable X is not known to be normally distributed, has a mean of size 8 and a variance of size 1.5, describe the sampling distribution of the sample mean for samples of size 30.

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Question 54

A sample of size 35 is taken from a normal population, with mean of 65 and standard deviation of 9.3. Describe the sampling distribution of the sample mean.

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Question 55

An infinite population has a mean of 33 and a standard deviation of 6. A sample of 100 observations is to be taken at random from this population. The probability that the sample mean will be between 34.5 and 36.1 is: A. 0.1543. B. 0.2960. C. 0.6046. D. 0.4503.

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Question 56

The following table gives the number of pets owned for a population of four families. Family A B C D Number of pets owned 2 1 4 3 Samples of size 2 will be drawn at random from the population. Use your answers to the previous question to calculate the mean and the standard deviation of the sampling distribution of the sample means.

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Question 57

It is know that 40% of voters in a certain electorate are in favour of a particular candidate. If a sample of size 30 is taken, what is the probability that less than 35% are in favour of this political candidate? A. 40\% B. Less than 0.10\% C. 28.77\% D. None of these choices are correct.

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Question 58

Random samples of size 81 are taken from an infinite population whose mean and standard deviation are 45 and 9, respectively. The mean and standard error of the sampling distribution of the sample mean are: A. 9 and 45. B. 45 and 9. C. 81 and 45. D. 45 and 1.

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Question 59

As a general rule in computing the standard error of the sample mean, the finite population correction factor is used only if the: A sample size is smaller than 10 \% of the population size. B population size is smaller than 10\% of the sample size. C sample size is greater than 1\% of the population size. D population size is greater than 1\% of the sample size.

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Question 60

The expected value of the sampling distribution of the sample mean $\bar { X }$ equals the population mean $\mu$ : A when the population is normally distributed. B when the population is symmetric. C when the population size N>30 . D for all populations.

The sampling distribution of the sample proportion has mean p and variance pq/n.

If the daily demand for boxes of mineral water at a supermarket is normally distributed with a mean of 47.6 boxes and a standard deviation of 5.8 boxes, what is the probability that the average demand for a sample of 10 supermarkets will be less than 50 boxes in a given day?

If a random sample of size n is drawn from a normal population, then the sampling distribution of the sample mean $\bar { X }$ will be: A normal for all values of n . B normal only for n>30 . C approximately normal for all values of n . D approximately normal only for n>30 .

Random samples of size 64 are taken from an infinite population whose mean is 160 and standard deviation is 32. The mean and standard error of the sample mean, respectively, are: A. 160 and 32. B. 64 and 32. C. 160 and 4. D. 20 and 4.

The standard deviation of the sampling distribution of the sample mean is also called the: A central limit theorem. B standard error of the mean. C finite population correction factor. D population standard deviation.

If all possible samples of size n are drawn from an infinite population with a mean of 15 and a standard deviation of 5, then the standard error of the sample mean equals 1.0 only for samples of size: A. 5. B. 15. C. 25. D. 75.

Consider an infinite population with a mean of 100 and a standard deviation of 20. A random sample of size 50 is taken from this population. The standard deviation of the sample mean equals 3.2.

An infinite population has a mean of 100 and a standard deviation of 20. Suppose that the population is not normally distributed. What does the central limit theorem say about the sampling distribution of the mean if samples of size 64 are drawn at random from this population?

The following table gives the number of pets owned for a population of four families. Family A B C D Number of pets owned 2 1 4 3 Find the sampling distribution of $\bar { X }$ .

If a random variable X is not known to be normally distributed, has a mean of size 8 and a variance of size 1.5, describe the sampling distribution of the sample mean for samples of size 30.

A sample of size 35 is taken from a normal population, with mean of 65 and standard deviation of 9.3. Describe the sampling distribution of the sample mean.

An infinite population has a mean of 33 and a standard deviation of 6. A sample of 100 observations is to be taken at random from this population. The probability that the sample mean will be between 34.5 and 36.1 is: A. 0.1543. B. 0.2960. C. 0.6046. D. 0.4503.

It is know that 40% of voters in a certain electorate are in favour of a particular candidate. If a sample of size 30 is taken, what is the probability that less than 35% are in favour of this political candidate? A. 40\% B. Less than 0.10\% C. 28.77\% D. None of these choices are correct.

Random samples of size 81 are taken from an infinite population whose mean and standard deviation are 45 and 9, respectively. The mean and standard error of the sampling distribution of the sample mean are: A. 9 and 45. B. 45 and 9. C. 81 and 45. D. 45 and 1.

What Is Statistics

Types of Data, Data Collection and Sampling

Graphical Descriptive Methods Nominal Data

Graphical Descriptive Techniques Numerical Data

Numerical Descriptive Measures

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Introduction

Estimation: Describing a Single Population

Estimation: Comparing Two Populations

Hypothesis Testing: Describing a Single Population

Hypothesis Testing: Comparing Two Populations

Inference About Population Variances

Analysis of Variance

Additional Tests for Nominal Data: Chi-Squared Tests

Simple Linear Regression and Correlation

Multiple Regression

Model Building

Nonparametric Techniques

Statistical Inference: Conclusion

Time-Series Analysis and Forecasting

Index Numbers

Decision Analysis

Filters

Exam 10: Sampling Distributions

The expected value of the sampling distribution of the sample mean Xˉ\bar { X }Xˉ equals the population mean μ\muμ : A when the population is normally distributed. B when the population is symmetric. C when the population size N>30 . D for all populations.

The sampling distribution of the sample proportion has mean p and variance pq/n.

If the daily demand for boxes of mineral water at a supermarket is normally distributed with a mean of 47.6 boxes and a standard deviation of 5.8 boxes, what is the probability that the average demand for a sample of 10 supermarkets will be less than 50 boxes in a given day?

If a random sample of size n is drawn from a normal population, then the sampling distribution of the sample mean Xˉ\bar { X }Xˉ will be: A normal for all values of n . B normal only for n>30 . C approximately normal for all values of n . D approximately normal only for n>30 .

Random samples of size 64 are taken from an infinite population whose mean is 160 and standard deviation is 32. The mean and standard error of the sample mean, respectively, are: A. 160 and 32. B. 64 and 32. C. 160 and 4. D. 20 and 4.

The standard deviation of the sampling distribution of the sample mean is also called the: A central limit theorem. B standard error of the mean. C finite population correction factor. D population standard deviation.

If all possible samples of size n are drawn from an infinite population with a mean of 15 and a standard deviation of 5, then the standard error of the sample mean equals 1.0 only for samples of size: A. 5. B. 15. C. 25. D. 75.

Consider an infinite population with a mean of 100 and a standard deviation of 20. A random sample of size 50 is taken from this population. The standard deviation of the sample mean equals 3.2.

An infinite population has a mean of 100 and a standard deviation of 20. Suppose that the population is not normally distributed. What does the central limit theorem say about the sampling distribution of the mean if samples of size 64 are drawn at random from this population?

The following table gives the number of pets owned for a population of four families. Family A B C D Number of pets owned 2 1 4 3 Find the sampling distribution of Xˉ\bar { X }Xˉ .

If a random variable X is not known to be normally distributed, has a mean of size 8 and a variance of size 1.5, describe the sampling distribution of the sample mean for samples of size 30.

A sample of size 35 is taken from a normal population, with mean of 65 and standard deviation of 9.3. Describe the sampling distribution of the sample mean.

An infinite population has a mean of 33 and a standard deviation of 6. A sample of 100 observations is to be taken at random from this population. The probability that the sample mean will be between 34.5 and 36.1 is: A. 0.1543. B. 0.2960. C. 0.6046. D. 0.4503.

It is know that 40% of voters in a certain electorate are in favour of a particular candidate. If a sample of size 30 is taken, what is the probability that less than 35% are in favour of this political candidate? A. 40\% B. Less than 0.10\% C. 28.77\% D. None of these choices are correct.

Random samples of size 81 are taken from an infinite population whose mean and standard deviation are 45 and 9, respectively. The mean and standard error of the sampling distribution of the sample mean are: A. 9 and 45. B. 45 and 9. C. 81 and 45. D. 45 and 1.

What Is Statistics

Types of Data, Data Collection and Sampling

Graphical Descriptive Methods Nominal Data

Graphical Descriptive Techniques Numerical Data

Numerical Descriptive Measures

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Introduction

Estimation: Describing a Single Population

Estimation: Comparing Two Populations

Hypothesis Testing: Describing a Single Population

Hypothesis Testing: Comparing Two Populations

Inference About Population Variances

Analysis of Variance

Additional Tests for Nominal Data: Chi-Squared Tests

Simple Linear Regression and Correlation

Multiple Regression

Model Building

Nonparametric Techniques

Statistical Inference: Conclusion

Time-Series Analysis and Forecasting

Index Numbers

Decision Analysis

Filters

The expected value of the sampling distribution of the sample mean $\bar { X }$ equals the population mean $\mu$ : A when the population is normally distributed. B when the population is symmetric. C when the population size N>30 . D for all populations.

If a random sample of size n is drawn from a normal population, then the sampling distribution of the sample mean $\bar { X }$ will be: A normal for all values of n . B normal only for n>30 . C approximately normal for all values of n . D approximately normal only for n>30 .

The following table gives the number of pets owned for a population of four families. Family A B C D Number of pets owned 2 1 4 3 Find the sampling distribution of $\bar { X }$ .