Chapter 7 & 8 terms from book

t distribution

A family of probability distributions that can be used to develop an interval estimate of a population mean whenever the population standard deviation σ is unknown and is estimated by the sample standard deviation s.

frame

A listing of the elements the sample will be selected from.

judgment sampling

A nonprobability method of sampling whereby elements are selected for the sample based on the judgment of the person doing the study.

convenience sampling

A nonprobability method of sampling whereby elements are selected for the sample on the basis of convenience.

parameter

A numerical characteristic of a population, such as a population mean μ, a population standard deviation σ, a population proportion p, and so on.

degrees of freedom

A parameter of the t distribution. When the t distribution is used in the computation of an interval estimate of a population mean, the appropriate t distribution has n-1 degrees of freedom, where n is the size of the sample.

sampling distribution

A probability distribution consisting of all possible values of a sample statistic.

cluster sampling

A probability sampling method in which the population is first divided into clusters and then a simple random sample of the clusters is taken.

stratified random sampling

A probability sampling method in which the population is first divided into strata and a simple random sample is then taken from each stratum.

systematic sampling

A probability sampling method in which we randomly select one of the first k elements and then select every kth element thereafter.

unbiased

A property of a point estimator that is present when the expected value of the point estimator is equal to the population parameter it estimates.

random sample

A random sample from an infinite population is a sample selected such that the following conditions are satisfied: (1) Each element selected comes from the same population; (2) each element is selected independently.

sample statistic

A sample characteristic, such as a sample mean x̅ , sample standard deviation s, a sample proportion p, and so on. The value of the sample statistic is used to estimate the value of the corresponding population parameter.

simple random sample

A simple random sample of size n from a finite population of size N is a sample selected such that each possible sample of size n has the same probability of being selected.

central limit theorem

A theorem that enables one to use the normal probability distribution to approximate the sampling distribution of x̅ whenever the sample size is large

interval estimate

An estimate of a population parameter that provides an interval believed to contain the value of the parameter. For the interval estimates in this chapter, it has the form: point estimate ± margin of error.

confidence interval

Another name for an interval estimate.

confidence level

The confidence associated with an interval estimate. For example, if an interval estimation procedure provides intervals such that 95% of the intervals formed using the procedure will include the population parameter, the interval estimate is said to be constructed at the 95% confidence level.

sampling without replacement

Once an element has been included in the sample, it is removed from the population and cannot be selected a second time.

sampling with replacement

Once an element has been included in the sample, it is returned to the population. A previously selected element can be selected again and therefore may appear in the sample more than once.

σ known

The case when historical data or other information provides a good value for the population standard deviation prior to taking a sample. The interval estimation procedure uses this known value of σ in computing the margin of error.

confidence coefficient

The confidence level expressed as a decimal value. For example, .95 is the confidence coefficient for a 95% confidence level.

σ unknown

The more common case when no good basis exists for estimating the population standard deviation prior to taking the sample. The interval estimation procedure uses the sample standard deviation s in computing the margin of error.

target population

The population for which statistical inferences such as point estimates are made. It is important for the target population to correspond as closely as possible to the sampled population.

sampled population

The population from which the sample is taken.

point estimator

The sample statistic, such as x̅ , s, or p, that provides the point estimate of the population parameter.

standard error

The standard deviation of a point estimator.

point estimate

The value of a point estimator used in a particular instance as an estimate of a population parameter.

margin of error

The ± value added to and subtracted from a point estimate in order to develop an interval estimate of a population parameter.

finite population correction factor

the equation used to find σx̅ and σp̂, whenever a finite population, rather than an infinite population, is being sampled. The generally accepted rule of thumb is to ignore the finite population correction factor whenever n/N ≤ .05