Question 1

Estimation is the process of inferring the value of an unknown population parameter using data from a random sample

Accepted Answer

A) True 
 B)False

Question 2

A simple random sample is one where each member of the population has a known chance (this may differ from one member to another)or probability of being chosen.

Accepted Answer

A) True 
 B)False

Question 3

Ideally,we prefer estimates that have large standard errors.

Accepted Answer

A) True 
 B)False

Question 4

When we sample less than 5% of the population,the finite population correction factor;fpc = $\sqrt { ( N - n ) / ( N - 1 ) }$ 
,is used to modify the formula for the standard error of the sample mean.

Accepted Answer

A) True 
 B)False

Question 5

If systematic sampling is chosen as the sampling technique,it is probably because:

Accepted Answer

A)  Systematic sampling has better statistical properties than simple random sampling 
B)  Systematic sampling is more convenient 
C)  Systematic sampling always results in more representative sampling than simple random sampling 
D)  None of these options 
A)  Systematic sampling has better statistical properties than simple random sampling 
B)  Systematic sampling is more convenient 
C)  Systematic sampling always results in more representative sampling than simple random sampling 
D)  None of these options

Question 6

The standard error of sample mean $x$ 
is large when the observations in the population are spread out (large $\sigma$ 
),but that the standard error can be reduced by taking a smaller sample.

Accepted Answer

A) True 
 B)False

Question 7

The approximate 95% confidence interval for a population mean is:

Accepted Answer

A) 
$x \pm \sigma / \sqrt { n }$ 
B) 
$x \pm s / \sqrt { n }$ 
C) 
$$X \pm 2 \sigma / \sqrt { n }$$ 
D) 
$x \pm 2 s l \sqrt { n }$ 
A) 
$x \pm \sigma / \sqrt { n }$ 
B) 
$x \pm s / \sqrt { n }$ 
C) 
$$X \pm 2 \sigma / \sqrt { n }$$ 
D) 
$x \pm 2 s l \sqrt { n }$

Question 8

The Central Limit Theorem (CLT)says that as long as the sample size is reasonably large,there is about a 95% chance that the magnitude of the sampling error for the mean will be no more than two standard errors.

Accepted Answer

A) True 
 B)False

Question 9

A sample of size 20 is selected at random from a population of size N.If the finite population correction factor is 0.9418,then N must be 169.

Accepted Answer

A) True 
 B)False

Question 10

Which of the following statements correctly describe estimation?

Accepted Answer

A)  It is the process of inferring the values of known population parameters from those of unknown sample statistics. 
B)  It is the process of inferring the values of unknown sample statistics from those of known population parameters. 
C)  It is the process of inferring the values of known sample statistics from those of unknown population parameters. 
D)  It is the process of inferring the values of unknown population parameters from those of known sample statistics. 
A)  It is the process of inferring the values of known population parameters from those of unknown sample statistics. 
B)  It is the process of inferring the values of unknown sample statistics from those of known population parameters. 
C)  It is the process of inferring the values of known sample statistics from those of unknown population parameters. 
D)  It is the process of inferring the values of unknown population parameters from those of known sample statistics.

Question 11

Sampling error is evident when:

Accepted Answer

A)  a question is poorly worded 
B)  the sample is too small 
C)  the sample is not random 
D)  the sample mean differs from the population mean 
A)  a question is poorly worded 
B)  the sample is too small 
C)  the sample is not random 
D)  the sample mean differs from the population mean

Question 12

A probability sample is a sample in which the sampling units are chosen from the population by means of a random mechanism such as a random number table.

Accepted Answer

A) True 
 B)False

Question 13

The averaging effect means that as you average more and more observations from a given distribution,the variance of the average

Accepted Answer

A)  increases 
B)  decreases 
C)  is unaffected 
D)  could either increase,decrease or stay the same 
A)  increases 
B)  decreases 
C)  is unaffected 
D)  could either increase,decrease or stay the same

Question 14

The probability of being chosen in a simple random sample of size n from a population of size N is:

Accepted Answer

A)  1/N 
B)  N - 1/n 
C)  N/n 
D)  n/N 
A)  1/N 
B)  N - 1/n 
C)  N/n 
D)  n/N

Question 15

Potential sample members,called sampling units,are:

Accepted Answer

A)  people 
B)  companies 
C)  households 
D)  All of these options 
A)  people 
B)  companies 
C)  households 
D)  All of these options

Question 16

A sample chosen in such a way that every possible subset of same size has an equal chance of being selected is called a(n)

Accepted Answer

A)  interval estimation 
B)  point estimation 
C)  simple random sample. 
D)  statistic 
A)  interval estimation 
B)  point estimation 
C)  simple random sample. 
D)  statistic

Question 17

Measurement error occurs when:

Accepted Answer

A)  a portion of the sample does not respond to the survey 
B)  the sample responses are not clear 
C)  the responses to question do not reflect what the investigator had in mind 
D)  the investigator does not correctly tally all responses 
A)  a portion of the sample does not respond to the survey 
B)  the sample responses are not clear 
C)  the responses to question do not reflect what the investigator had in mind 
D)  the investigator does not correctly tally all responses

Question 18

A list of all members of the population is called a:

Accepted Answer

A)  sampling unit 
B)  probability sample 
C)  frame 
D)  relevant population 
A)  sampling unit 
B)  probability sample 
C)  frame 
D)  relevant population

Question 19

Simple random samples are typically used in real applications.

Accepted Answer

A) True 
 B)False

Question 20

One obvious advantage of stratified sampling is that we obtain separate estimates within each stratum - which we would not obtain if we took a simple random sample from the entire population.A more important advantage is that we can increase the accuracy of the resulting population estimates by using appropriately defined strata.

Accepted Answer

A) True 
 B)False

Estimation is the process of inferring the value of an unknown population parameter using data from a random sample

A simple random sample is one where each member of the population has a known chance (this may differ from one member to another)or probability of being chosen.

Ideally,we prefer estimates that have large standard errors.

When we sample less than 5% of the population,the finite population correction factor;fpc = $\sqrt { ( N - n ) / ( N - 1 ) }$ ,is used to modify the formula for the standard error of the sample mean.

If systematic sampling is chosen as the sampling technique,it is probably because:

The standard error of sample mean $x$ is large when the observations in the population are spread out (large $\sigma$ ),but that the standard error can be reduced by taking a smaller sample.

The approximate 95% confidence interval for a population mean is:

The Central Limit Theorem (CLT)says that as long as the sample size is reasonably large,there is about a 95% chance that the magnitude of the sampling error for the mean will be no more than two standard errors.

A sample of size 20 is selected at random from a population of size N.If the finite population correction factor is 0.9418,then N must be 169.

Which of the following statements correctly describe estimation?

Sampling error is evident when:

A probability sample is a sample in which the sampling units are chosen from the population by means of a random mechanism such as a random number table.

The averaging effect means that as you average more and more observations from a given distribution,the variance of the average

The probability of being chosen in a simple random sample of size n from a population of size N is:

Potential sample members,called sampling units,are:

A sample chosen in such a way that every possible subset of same size has an equal chance of being selected is called a(n)

Measurement error occurs when:

A list of all members of the population is called a:

Simple random samples are typically used in real applications.

Introduction to Data Analysis and Decision Making

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, Binomial, Poisson, and Exponential Distributions

Decision Making Under Uncertainty

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

Exam 7: Sampling and Sampling Distributions

Estimation is the process of inferring the value of an unknown population parameter using data from a random sample

A simple random sample is one where each member of the population has a known chance (this may differ from one member to another)or probability of being chosen.

Ideally,we prefer estimates that have large standard errors.

When we sample less than 5% of the population,the finite population correction factor;fpc = (N−n)/(N−1)\sqrt { ( N - n ) / ( N - 1 ) }(N−n)/(N−1)​ ,is used to modify the formula for the standard error of the sample mean.

If systematic sampling is chosen as the sampling technique,it is probably because:

The standard error of sample mean xxx is large when the observations in the population are spread out (large σ\sigmaσ ),but that the standard error can be reduced by taking a smaller sample.

The approximate 95% confidence interval for a population mean is:

The Central Limit Theorem (CLT)says that as long as the sample size is reasonably large,there is about a 95% chance that the magnitude of the sampling error for the mean will be no more than two standard errors.

A sample of size 20 is selected at random from a population of size N.If the finite population correction factor is 0.9418,then N must be 169.

Which of the following statements correctly describe estimation?

Sampling error is evident when:

A probability sample is a sample in which the sampling units are chosen from the population by means of a random mechanism such as a random number table.

The averaging effect means that as you average more and more observations from a given distribution,the variance of the average

The probability of being chosen in a simple random sample of size n from a population of size N is:

Potential sample members,called sampling units,are:

A sample chosen in such a way that every possible subset of same size has an equal chance of being selected is called a(n)

Measurement error occurs when:

A list of all members of the population is called a:

Simple random samples are typically used in real applications.

Introduction to Data Analysis and Decision Making

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, Binomial, Poisson, and Exponential Distributions

Decision Making Under Uncertainty

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

When we sample less than 5% of the population,the finite population correction factor;fpc = $\sqrt { ( N - n ) / ( N - 1 ) }$ ,is used to modify the formula for the standard error of the sample mean.

The standard error of sample mean $x$ is large when the observations in the population are spread out (large $\sigma$ ),but that the standard error can be reduced by taking a smaller sample.