Transcript Welcome to AP Statistics!

AP Statistics
C5 D2
HW: p.287 #25 – 30
Obj: to understand types of samples and
possible errors
Do Now:
How do you think you collect data?
Sampling Designs
• SRS (ensure that each individual has an equal
chance of being selected for the sample AND
that each subset has an equal chance of being
the sample)
• Convenience sample
• Quota sampling
-ensure that you have a certain # from each
group of interest within the population
-Ex: If you have a class that is 30% girls and
70% boys, you may want to choose a sample of
size 10 that includes 3 girls and 7 boys.
Probability Samples
• SRS is one type – each element has an equal
probability of being selected
• Stratified Random Sample
- the population is divided into
homogeneous groups (ex: urban,
suburban, rural) called strata
- get an SRS from each strata, then put all
SRS together to form a sample
- this ensures that all groups within a
population are represented
• Multistage Cluster Sample
Ex: Suppose we want a sample of US households’
weekly spending on groceries.
It would be a lot of work and cost a lot of money
to take an SRS of households across the
country.
One day you might have to go to a house in
Cleveland and the next day you have to go to
New York, etc.
Instead you could take a multistage cluster
sample:
1. Take an SRS of states in the US.
2. Take an SRS of towns within the states
selected in stage 1.
3. Take an SRS of the streets in the towns
selected in stage 2.
4. Take an SRS of the houses on the
streets selected in stage 4.
This way, you end up interviewing 20
households on one block instead of 1
households on 20 blocks
Multistage cluster sampling can be very
efficient and cost effective while making
sure that your sample is still randomly
selected.
• Systematic Random Sample
- Survey every 50th person who walks by.
Errors
• Sample frame error - when sample frame
(list of possible subjects who could be
selected in a sample) does not represent
the population.
• Random sample error – chance variation
(sample of students from this school just
happens to contain only boys)
• Sampling method error – choosing the
wrong method (convenience sampling)
Errors
• Response bias – wording of questions,
order of answer choices, behavior of
interviewer, dishonesty in responses
• Sample size is too small – larger samples
give more accurate results