Interval Estimation

The margin of error in an interval estimate of the population mean is a function of:

-a -sample mean -sample size -->>> not for "variability of the population"

The sampling distribution of the mean (x barred)

can be used to compute the probability that mean (x barred) will be a given distance from M

A point estimate

cannot be expected to provide the exact value of the population parameter

t distribution

depends on a parameter known as degrees of freedom

An estimate of a population parameter that provides an interval of values believed to contain the value of the parameter is known as the

interval estimate

The value added to and subtracted from a point estimate in order to develop an interval estimate of the population parameter is known as the

planning value

The probability that the interval estimation procedure will generate an interval that does NOT contain the actual value of the population parameter being estimated is the

same as a

When s is used to estimate o', the margin of error is computed by using the

t distribution

as the number of degrees of freedom increases,

the difference of the t distribution and the standard normal distribution becomes smaller and smaller

An interval estimate is calculated by

(Point Estimate - Margin of Error) ; (Point Estimate + Margin of Error)

If we want to provide a 95% confidence interval for the mean of a population, the confidence coefficient will be

.95

the mean of the t distribution is

0

A random sample of 25 employees of a local company has been taken. A 95% confidence interval estimate for the mean systolic blood pressure for all employees of the company is 123 139. Which if the following statement is valid?

If the sampling procedure were repeated many times, 95% of the resulting confidence intervals would contain the population mean systolic blood pressure

In interval estimation, as the sample size becomes larger, the interval estimate

becomes narrower

As the number of degrees of freedom for a t distribution increases, the difference between the t distribution and the standard normal distribution

becomes smaller

The ability of an interval estimate to contain the value of the population parameter is described by the

confidence level

The t distribution is a family of similar probability distributions, with each individual distribution depending on a parameter known as the

degrees of freedom

A 95% confidence interval for a population mean is determines to be 100 to 120. For the same data, if the confidence coefficient is reduced to .90, the confidence interval

for M becomes narrower

For a given confidence level and when sigma is known, the margin of error in a confidence interval estimate

is the same for all samples of the same size

A t distribution with more degrees of freedom has

less dispersion

A sample of 200 elements from a population with a known standard deviation is selected. For an interval estimation of M, the proper distribution to use is the

normal distribution

The purpose of an interval estimate is to

provide information about how close the point estimate is to the value of the population parameter

From a population the is normally distributed, a sample of 25 elements is selected and the standard deviation of the sample is computed. For the interval estimation of M, the proper distribution to use is the

t distribution with 24 degrees of freedom

Degrees of Freedom (df) refers to

the number of independent pieces of information that go into the computation of ∑(xi - ×)² , which is part of the sample variance s

In interval estimation, the t distribution is applicable only when

the sample standard deviation is used to estimate the population standard deviation