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32 terms

sampling frame

a listing of items that make up the population

Frames

data sources such as population lists, directories, or maps

Inaccurate or biased results can result if

a frame excludes certain portions of the population

convenience sampling

items are selected based only on the fact that they are easy, inexpensive, or convenient to sample

judgment sample

you get the opinions of pre-selected experts in the subject matter

nonprobability sample

items included are chosen without regard to their probability of occurrence.

probability sample

items in the sample are chosen on the basis of known probabilities

Simple random sample and Systematic sample

1. Simple to use

2. May not be a good representation of the population's underlying characteristics

2. May not be a good representation of the population's underlying characteristics

Stratified sample

Ensures representation of individuals across the entire population

Cluster sample

1. More cost effective

2. Less efficient (need larger sample to acquire the same level of precision)

2. Less efficient (need larger sample to acquire the same level of precision)

Coverage error or selection bias

Exists if some groups are excluded from the frame and have no chance of being selected

Non response error or bias

People who do not respond may be different from those who do respond

Sampling error

Variation from sample to sample will always exist

Measurement error

Due to weaknesses in question design, respondent error, and interviewer's effects on the respondent

sampling distribution

is a distribution of all of the possible values of a sample statistic for a given size sample selected from a population

Different samples of the same size from the same population will yield

different sample means

Standard Error of the Mean

A measure of the variability in the mean from sample to sample

standard error of the mean decreases

as the sample size increases

As the sample size gets large enough...(Central Limit Theorem)

the sampling distribution becomes almost normal regardless of shape of population

True or False: Sampling error becomes an ethical issue if the findings are purposely presented without reference to sample size and margin of error so that the sponsor can promote a viewpoint that might otherwise be truly insignificant.

True

For sample size 16, the sampling distribution of the mean will be approximately normally distributed

if the shape of the population is symmetrical.

True or False: A sample is selected by including everybody who sits in the first row of a business statistics class. This is an example of a cluster sample.

true

For sample size 1, the sampling distribution of the mean will be normally distributed

only if the population is normally distributed.

True or False: Systematic samples are less efficient than stratified sample.

True

types of samples can you use if you want to make valid statistical inferences from a sample to a population?

A probability sample

True or False: A sample is always a good representation of the target population.

False

True or False: Chunk sample is a type of probability sample.

False

True or False: The question "How many times have you abused your spouse in the last 6 months?" will most likely result in nonresponse error.

True

True or False: As a population becomes large, it is usually better to obtain statistical information from the entire population.

False

True or False: The question: "How much did you make last year rounded to the nearest hundreds of dollars?" will most likely result in measurement error.

True

True or False: The only way one can eliminate sampling error is to take the whole population as the sample.

True

True or False: The only reliable way a researcher can make statistical inferences from a sample to a population is to use nonprobability sampling methods.

False