Which of the following is not a part of the formula for constructing a confidence interval estimate of the population mean? $\begin{array}{|l|l|} \hline A&\text { A point estimate of the population mean.}\\ \hline B&\text {The standard error of the sampling distribution of the sample mean. }\\ \hline C&\text { The confidence level.}\\ \hline D&\text {The value of the population mean. }\\ \hline \end{array}$

The answer of Which of the following is not a...

From a sample of 300 items, 15 are defective. The point estimate of the population proportion defective will be: $\begin{array}{|l|l|} \hline\text { A. } & 0.05 \\ \hline \text { B. } & 15 . \\ \hline \text { C. } & 0.20 \\ \hline \text { D. } & 0.05-0.10 \\ \hline \end{array}$

The answer of From a sample of 300 items, 15...

The objective of estimation is to determine the approximate value of: $\begin{array}{|l|l|} \hline A&\text {a sample statistic. }\\ \hline B&\text { a population parameter.}\\ \hline C&\text {the sample mean. }\\ \hline D&\text { the sample variance.}\\ \hline \end{array}$

The answer of The objective of estimation is to determine...

If the Student t distribution is incorrectly used instead of the Standard normal distribution when finding the confidence interval for the population mean, and the population variance was known, what will happen to the width of the confidence interval? $\begin{array}{|l|l|} \hline A&\text {The confidence interval would have the same width. }\\ \hline B&\text { The confidence interval would be wider than it should be, as t is flatter than \( Z $. }\\ \hline C&\text { The confidence interval will be narrower than it should be as $ t $ is flatter than $ Z $. }\\ \hline D&\text { None of these choices are correct.}\\ \hline \end{array}\)

The answer of If the Student t distribution is incorrectly...

Exam 11: Estimation: Describing a Single Population

A 90% confidence interval estimate of the population mean $\mu$ can be interpreted to mean that: A if we repeatedly draw samples of the same size from the same population, 90 \% of the values of the sample means will result in a confidence interval that includes the population mean. B there is a 90\% probability that the population mean will lie between the lower confidence limit (LCL) and the upper confidence limit (UCL). C we are 90\% confident that we have selected a sample whose range of values does not contain the population mean. D We are 90\% confident that 10\% the values of the sample means will result in a confidence interval that includes the population mean.

(Short Answer)

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Question 61

The percentage of the confidence interval relies on the significance level. $\alpha$

(True/False)

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Question 62

Suppose that a 95% confidence interval for $\mu$ is given by $\bar { x } \pm 3.25$ . This notation means that if we repeatedly draw samples of the same size from the same population, 95% of the values of $\bar { x }$ will be such that $\mu$ would lie somewhere between $\bar { x } - 325$ and $\bar { x } + 325$ .

(True/False)

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Question 63

You need four values to construct the confidence interval estimate of $\mu$ . These are the sample mean, sample size, population standard deviation and confidence level.

(True/False)

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Question 64

A 95% confidence interval estimate for a population mean $\mu$ is determined to be 75 to 85. If the confidence level is reduced to 80%, the confidence interval for $\mu$ becomes narrower.

(True/False)

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Question 65

The standard error of the sampling distribution of the sample proportion $\hat { p }$ , when the sample size n = 100 and the population proportion p = 0.30, is 0.0021.

(True/False)

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Question 66

A random sample of 10 waitresses in Darwin revealed the following hourly earnings (in dollars, including tips): 19 18 15 16 18 17 16 18 20 14 If the hourly earnings are normally distributed with a standard deviation of $4.5, estimate with 95% confidence the mean hourly earnings for all waitresses in Darwin.

(Short Answer)

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Question 67

Which of the following is not a part of the formula for constructing a confidence interval estimate of the population mean? A A point estimate of the population mean. B The standard error of the sampling distribution of the sample mean. C The confidence level. D The value of the population mean.

(Short Answer)

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Question 68

Suppose that your task is to estimate the mean of a normally distributed population to within 10 units with 95% confidence and that the population standard deviation is known to be 70. What sample size should you use with a 90% confidence level?

(Short Answer)

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Question 69

From a sample of 300 items, 15 are defective. The point estimate of the population proportion defective will be: A. 0.05 B. 15. C. 0.20 D. 0.05-0.10

(Short Answer)

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Question 70

The probability of a success on any trial of a binomial experiment is 0.15. Find the probability that the proportion of success in a sample of 300 is more than 12%.

(Short Answer)

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Question 71

The objective of estimation is to determine the approximate value of: A a sample statistic. B a population parameter. C the sample mean. D the sample variance.

(Short Answer)

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Question 72

Suppose that the amount of time teenagers spend on the Internet is normally distributed, with a standard deviation of 1.5 hours. A sample of 100 teenagers is selected at random, and the sample mean is computed as 6.5 hours. Interpret what the confidence interval estimate tells you.

(Essay)

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Question 73

The sample variance $s ^ { 2 }$ is an unbiased estimator of the population variance $\sigma ^ { 2 }$ when the denominator of $s ^ { 2 }$ is n - 1.

(True/False)

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Question 74

Which of the following statements is (are) true? A The sample mean is relatively more efficient than the sample median. B The sample median is relatively more efficient than the sample mean. C The sample variance is relatively more efficient than the sample variance. D All of these choices are correct.

(Short Answer)

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Question 75

The upper limit of the 90% confidence interval for $\mu$ , given that n = 64, $\bar { x }$ = 70 and $\sigma$ = 20, is 65.89.

(True/False)

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Question 76

If the Student t distribution is incorrectly used instead of the Standard normal distribution when finding the confidence interval for the population mean, and the population variance was known, what will happen to the width of the confidence interval? A The confidence interval would have the same width. B The confidence interval would be wider than it should be, as t is flatter than Z . C The confidence interval will be narrower than it should be as t is flatter than Z . D None of these choices are correct.

(Short Answer)

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Question 77

The difference between the sample statistic and actual value of the population parameter is the percentage of the confidence interval.

(True/False)

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Question 78

When constructing confidence interval for a parameter, we generally set the confidence level $1 - \alpha$ close to 1 (usually between 0.90 and 0.99) because we would like to be reasonably confident that the interval includes the actual value of the population parameter.

(True/False)

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Question 79

The sample mean $\bar { x }$ is a consistent estimator of the population mean $\mu$ .

(True/False)

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Question 80

The percentage of the confidence interval relies on the significance level. $\alpha$

You need four values to construct the confidence interval estimate of $\mu$ . These are the sample mean, sample size, population standard deviation and confidence level.

A 95% confidence interval estimate for a population mean $\mu$ is determined to be 75 to 85. If the confidence level is reduced to 80%, the confidence interval for $\mu$ becomes narrower.

The standard error of the sampling distribution of the sample proportion $\hat { p }$ , when the sample size n = 100 and the population proportion p = 0.30, is 0.0021.

Which of the following is not a part of the formula for constructing a confidence interval estimate of the population mean? A A point estimate of the population mean. B The standard error of the sampling distribution of the sample mean. C The confidence level. D The value of the population mean.

Suppose that your task is to estimate the mean of a normally distributed population to within 10 units with 95% confidence and that the population standard deviation is known to be 70. What sample size should you use with a 90% confidence level?

From a sample of 300 items, 15 are defective. The point estimate of the population proportion defective will be: A. 0.05 B. 15. C. 0.20 D. 0.05-0.10

The probability of a success on any trial of a binomial experiment is 0.15. Find the probability that the proportion of success in a sample of 300 is more than 12%.

The objective of estimation is to determine the approximate value of: A a sample statistic. B a population parameter. C the sample mean. D the sample variance.

Suppose that the amount of time teenagers spend on the Internet is normally distributed, with a standard deviation of 1.5 hours. A sample of 100 teenagers is selected at random, and the sample mean is computed as 6.5 hours. Interpret what the confidence interval estimate tells you.

The sample variance $s ^ { 2 }$ is an unbiased estimator of the population variance $\sigma ^ { 2 }$ when the denominator of $s ^ { 2 }$ is n - 1.

The upper limit of the 90% confidence interval for $\mu$ , given that n = 64, $\bar { x }$ = 70 and $\sigma$ = 20, is 65.89.

The difference between the sample statistic and actual value of the population parameter is the percentage of the confidence interval.

When constructing confidence interval for a parameter, we generally set the confidence level $1 - \alpha$ close to 1 (usually between 0.90 and 0.99) because we would like to be reasonably confident that the interval includes the actual value of the population parameter.

The sample mean $\bar { x }$ is a consistent estimator of the population mean $\mu$ .

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

Sampling Distributions

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 11: Estimation: Describing a Single Population

The percentage of the confidence interval relies on the significance level. α\alphaα

You need four values to construct the confidence interval estimate of μ\muμ . These are the sample mean, sample size, population standard deviation and confidence level.

A 95% confidence interval estimate for a population mean μ\muμ is determined to be 75 to 85. If the confidence level is reduced to 80%, the confidence interval for μ\muμ becomes narrower.

The standard error of the sampling distribution of the sample proportion p^\hat { p }p^​ , when the sample size n = 100 and the population proportion p = 0.30, is 0.0021.

Which of the following is not a part of the formula for constructing a confidence interval estimate of the population mean? A A point estimate of the population mean. B The standard error of the sampling distribution of the sample mean. C The confidence level. D The value of the population mean.

Suppose that your task is to estimate the mean of a normally distributed population to within 10 units with 95% confidence and that the population standard deviation is known to be 70. What sample size should you use with a 90% confidence level?

From a sample of 300 items, 15 are defective. The point estimate of the population proportion defective will be: A. 0.05 B. 15. C. 0.20 D. 0.05-0.10

The probability of a success on any trial of a binomial experiment is 0.15. Find the probability that the proportion of success in a sample of 300 is more than 12%.

The objective of estimation is to determine the approximate value of: A a sample statistic. B a population parameter. C the sample mean. D the sample variance.

Suppose that the amount of time teenagers spend on the Internet is normally distributed, with a standard deviation of 1.5 hours. A sample of 100 teenagers is selected at random, and the sample mean is computed as 6.5 hours. Interpret what the confidence interval estimate tells you.

The sample variance s2s ^ { 2 }s2 is an unbiased estimator of the population variance σ2\sigma ^ { 2 }σ2 when the denominator of s2s ^ { 2 }s2 is n - 1.

The upper limit of the 90% confidence interval for μ\muμ , given that n = 64, xˉ\bar { x }xˉ = 70 and σ\sigmaσ = 20, is 65.89.

The difference between the sample statistic and actual value of the population parameter is the percentage of the confidence interval.

When constructing confidence interval for a parameter, we generally set the confidence level 1−α1 - \alpha1−α close to 1 (usually between 0.90 and 0.99) because we would like to be reasonably confident that the interval includes the actual value of the population parameter.

The sample mean xˉ\bar { x }xˉ is a consistent estimator of the population mean μ\muμ .

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

Sampling Distributions

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 percentage of the confidence interval relies on the significance level. $\alpha$

You need four values to construct the confidence interval estimate of $\mu$ . These are the sample mean, sample size, population standard deviation and confidence level.

A 95% confidence interval estimate for a population mean $\mu$ is determined to be 75 to 85. If the confidence level is reduced to 80%, the confidence interval for $\mu$ becomes narrower.

The standard error of the sampling distribution of the sample proportion $\hat { p }$ , when the sample size n = 100 and the population proportion p = 0.30, is 0.0021.

The sample variance $s ^ { 2 }$ is an unbiased estimator of the population variance $\sigma ^ { 2 }$ when the denominator of $s ^ { 2 }$ is n - 1.

The upper limit of the 90% confidence interval for $\mu$ , given that n = 64, $\bar { x }$ = 70 and $\sigma$ = 20, is 65.89.

When constructing confidence interval for a parameter, we generally set the confidence level $1 - \alpha$ close to 1 (usually between 0.90 and 0.99) because we would like to be reasonably confident that the interval includes the actual value of the population parameter.

The sample mean $\bar { x }$ is a consistent estimator of the population mean $\mu$ .