AP Statistics Exam Study Guide Detailed
Questions And Expert Answers
How is a population measured?
a population is measured by a census.
How is a sample measured?
A sample is measured using a sampling technique, of which there are several.
Collecting data from an entire population is often impossible, infeasible, or beyond
the capability of the resources we have available. Samples can supply good
estimates of the population, and are much easier to collect data for.
Bias
anything that causes a sample to be not representative of the population of
interest.
· What is the difference between sampling error and sampling bias?
,Sampling error is an unavoidable phenomenon, because no sample can perfectly
represent the population. Sampling bias, however, is a systematic and avoidable
failure of the sample to at least be reasonably representative of the population.
How can a small sample size affect the validity of the sample?
Small sample sizes will result in high sampling error, thus reducing the usefulness
and applicability of the data.
Undercoverage
When one or more sub-groups within a population are not adequately
represented within the sample. This is particularly important if there is a
meaningful difference between which groups are represented and which aren't,
with regard to the research question.
Nonresponse bias
When the attempt is made to include all relevant sub-groups, but some groups fail
to respond or provide meaningful data. Again, particularly important if there is a
meaningful difference between which groups are providing responses and which
aren't.
Voluntary response bias
,When subjects are allowed to choose whether or not they are in the sample. This
tends to cause subjects with strong opinions to be overrepresented in the sample.
Loaded questions
When a question is designed in such a way to elicit a certain response, rather than
seeking to gather accurate information.
False answers
When the wording or nature of a question is such that subjects are unwilling or
unable to answer truthfully, and thus provide inaccurate or estimated data.
Simple Random Sample (SRS)
Randomly select n subjects from the population. Every subject has an equal chance
of being selected.
Stratified Random Sample
Separate the population into sub-groups (strata), then randomly select a certain
number of subjects from each group. Helps ensure important sub-groups are
represented
*Stratifying willreduce variabilityof possible sample results!
, Systematic Random Sample
The first subject is selected randomly. Then, every "nth" subject thereafter will be
sampled. The interval at which each subsequent subject will be selected is
determined in advance.
Cluster Sample
One or more subgroups that is reasonably representative of the population
("cluster") are selected and used as the sample.
Multistage Sample
More than one sampling technique is utilized in order to obtain the sample.
Convenience Sample
Subjects are selected based on how easy they are to obtain. Almost always leads
to biased results and should not be used if at all possible.
How to design a random sampling procedure
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