AP Statistics Exam Study Guide rated A
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.
Why do we often measure samples instead of populations? - 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.
,AP Statistics Exam Study Guide rated A
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.
,AP Statistics Exam Study Guide rated A
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.
, AP Statistics Exam Study Guide rated A
How to design a random sampling procedure - · Random number generator will be
your friend!
· "Describe a method..." (NOTE: blanks will be filled in with the context of the
problem!)
o START WITH: Assign each _________(unit, subject, etc.) a different number
between ____ and _____
o Describe how you will implement the sampling method you want to use
o Randomly select ________ numbers, ignoring repeats, and include the
_________(unit, subject, etc.) that corresponds with those numbers in your
sample.
A principal wants to create an advisory committee of 20 randomly-selected
students out of the 1,800 students their high school. Describe how he could do so
using a stratified random sample - Number all male students, then number all
female students. Randomly select 10 of the numbers assigned to the male
students and 10 of the numbers assigned to the female students.
A principal wants to create an advisory committee of 20 randomly-selected
students out of the 1,800 students their high school. Describe how he could do so
using a simple random sample - Number all 1800 students, then select 20 random
numbers (skipping repeats). The students corresponding with the selected #s will
be on the committee.
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.
Why do we often measure samples instead of populations? - 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.
,AP Statistics Exam Study Guide rated A
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.
,AP Statistics Exam Study Guide rated A
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.
, AP Statistics Exam Study Guide rated A
How to design a random sampling procedure - · Random number generator will be
your friend!
· "Describe a method..." (NOTE: blanks will be filled in with the context of the
problem!)
o START WITH: Assign each _________(unit, subject, etc.) a different number
between ____ and _____
o Describe how you will implement the sampling method you want to use
o Randomly select ________ numbers, ignoring repeats, and include the
_________(unit, subject, etc.) that corresponds with those numbers in your
sample.
A principal wants to create an advisory committee of 20 randomly-selected
students out of the 1,800 students their high school. Describe how he could do so
using a stratified random sample - Number all male students, then number all
female students. Randomly select 10 of the numbers assigned to the male
students and 10 of the numbers assigned to the female students.
A principal wants to create an advisory committee of 20 randomly-selected
students out of the 1,800 students their high school. Describe how he could do so
using a simple random sample - Number all 1800 students, then select 20 random
numbers (skipping repeats). The students corresponding with the selected #s will
be on the committee.
