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The level of significance

is (1 - confidence level)

The closer the sample mean is to the population mean,

the smaller the sampling error

After computing a confidence interval, the user believes the results are meaningless because the width of the interval is too large. Which one of the following is the best recommendation?

Increase the sample size.

In general, higher confidence levels provide

wider confidence intervals

Parameters are

numerical characteristics of a population

Convenience sampling is an example of

nonprobabilistic sampling

As the sample size increases, the

standard error of the mean decreases

The sample statistic, such as , s, or , that provides the point estimate of the population parameter is known as

a point estimator

Cluster sampling is

a probability sampling method

The absolute value of the difference between the point estimate and the population parameter it estimates is

the sampling error

Whenever the population standard deviation is unknown and the population has a normal or near-normal distribution, which distribution is used in developing an interval estimation?

t distribution

As the sample size increases, the margin of error


In determining the sample size necessary to estimate a population proportion, which of the following information is not needed?

the mean of the population

What type of error occurs if you fail to reject H0 when, in fact, it is not true?

Type II

The p-value is a probability that measures the support (or lack of support) for the

null hypothesis

The error of rejecting a true null hypothesis is

a Type I error

If a hypothesis is not rejected at the 5% level of significance, it

will also not be rejected at the 1% level

Whenever the population standard deviation is known which distribution is used in developing an interval estimation?

z distribution

A probability distribution for all possible values of a sample statistic is known as

a sampling distribution

A population characteristic, such as a population mean, is called

a parameter

A sample statistic, such as a sample mean, is known as

a statistic

The standard deviation of a point estimator is called the

standard error

A single numerical value used as an estimate of a population parameter is known as

a point estimate

A theorem that allows us to use the normal probability distribution to approximate the sampling distribution of sample means and sample proportions whenever the sample size is large is known as the

central limit theorem

The purpose of statistical inference is to provide information about the

population based upon information contained in the sample

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