AP Stats - 4.1 Quiz

1st step to explain how you took/created/separated a sample

Strata and Cluster: tell how you separated (ie: Separate all 120 students by age(2, 3, and 4)

SRS: LABEL

2nd step to explain how you took/created/separated a sample

Read the RDT x digits at a time.

3rd step to explain how you took/created/separated a sample

Ignore repeats and numbers outside the range

4th step to explain how you took/created/separated a sample

Indicate when to stop reading at (ie: Stop when 10 students are selected from each separated age group)

5th step to explain how you took/created/separated a sample

Identify the individuals chosen for the sample

What is an advantage of using stratified or cluster sampling over simple random sampling?

Stratified and/or cluster sampling makes the sample more random and less biased. In a simple random sampling, there is a greater change of sampling students from the same group, which results in a less diverse sample which leads to biased results and generalizations about populations.

population

the entire group of individuals we want info about(must be specific) ie: women who go to college in Florida

census

collects data from every individual in the population

sample

subset of individuals in the population from which we actually collect data

Convenience sample

choosing individuals from the population that are easy to reach; they are not random, which creates bias

stratified random sampling

classifying the population into groups of similar individuals (strata)

not all individuals in the chosen strata are used in the sample

Cluster sample

1. start by classifying the population into groups of individuals that are located near each other into clusters

2. Then choose an SRS of the clusters

3. All individuals in the chosen cluster are included

Systematic random sampling

1. Divide the population by desired sample size

2. The sample will be every nth person selected

   1. ie: if population is 100 and you want 5, select every 20th person

3. Gives each individual, not the sample, a equal chance of being chosen

Undercoverage bias

occurs when some members of the population cannot be chosen in a sample and portions of the population are excluded (ie: phone numbers - only using landline #’s)

Nonresponse bias

occurs when an individual chosen for the sample can’t be contacted or refuses to participate (ie: a person doesn’t answer their phone) must be random

Voluntary response bias

occurs when sample members are self-selected volunteers

Response bias

a systematic pattern of incorrect responses in a sample survey (ie: lying)

Wording of questions

confusing questions can change a person’s response and cause response bias