Chapter 7: Sampling - Estimating the Frequency of Behaviors and Beliefs

Question 1

Two most important validities for frequency claims

Answer 1

1. Construct validity: What survey questions were used?
   How did they operationalize their variables?
2. External validity: What sampling technique was used? (how did they get their sample)
   In what setting was the data collected?

Question 2

Population

Answer 2

The entire set of people or products in which you are interested.

Question 3

Sample

Answer 3

A smaller set taken from the population.

Question 4

Census

Answer 4

A set of observations that contains all members of the population of interest.

Question 5

Biased sample

Answer 5

Unrepresentative sample.
Some members of the population have a much higher probability of being included in the sample.
Not every participant had equal chance to make it to the sample stage!

Question 6

Representative sample

Answer 6

Unbiased sample.
All members of the population have an equal chance of being included in the sample (randomized).
Allow us to make inferences about the population of interest.

Question 7

Determining sample bias

Answer 7

1. Specify the population to which you want to generalize.
2. Look at how the sample was obtained - was it random or nonrandom? Random samples are representative, while nonrandom samples are unrepresentative of the population of interest.

Question 8

Convenience sampling

Answer 8

Sampling only those who are easy to contact and readily available to participate. Creates biased samples.

Question 9

Self-selection

Answer 9

Sample only those who volunteer. Creates biased samples.

Question 10

Probability sampling

Answer 10

Draw the sample at random from the population, every member has an equal chance of being in the sample, high external validity. AKA random/representative sampling.

Question 11

Simple random sampling

Answer 11

The most basic form of probability sampling, in which the sample is chosen completely at random from the population of interest. Examples include:

1. The names of every single member of the population are put into a hat and someone who is blind-folded pulls out names.
2. Random number generator.

Question 12

Systematic sampling

Answer 12

A probability sampling technique in which the researcher uses a randomly chosen number N (through RNG), and counts off every Nth member of a population to achieve a sample. Example: Start with the 4th person and sample every 7th person.

Question 13

Cluster sampling

Answer 13

Start with clusters, take a random sample of those clusters, and ALL members of those selected clusters are in your sample.
Example: Interested in college athletes in Virginia (population), start with a list of clusters (all colleges in Virginia), select a random sample of clusters (VCU, Roanoke College, William & Mary, UMW, JMU), and include all athletes from these identified colleges.

Question 14

Multistage sampling

Answer 14

Start with clusters, take a random sample of those clusters, then RANDOMLY sample from those selected clusters to get your sample. Example: Interested in college athletes in Virginia (population), start with a list of clusters (all colleges in Virginia), select a random sample of clusters (VCU, Roanoke College, William & Mary, UMW, JMU), and then randomly select athletes from these identified colleges.

Question 15

Stratified random sampling

Answer 15

Select particular demographic categories and randomly select people within each of these categories. Example: Interested in college athletes in Virginia (population), want to make sure to include equal male and female athletes, stratify the population based on gender, then randomly sample from each category.

Question 16

Oversampling

Answer 16

Randomly sample more participants of a specific group/category. Researcher intentionally over-represents one or more groups to ensure they are weighted to their actual proportion in the population.

Question 17

Random sampling

Answer 17

Draw a sample using a random method, which enhances external validity.

Question 18

Random assignment

Answer 18

Randomly place participants at different levels of the IV through experimental manipulation, which enhances internal validity.

Question 19

Purposive sampling

Answer 19

Seek out specific types of people/specific characteristics/traits.

Question 20

Snowball sampling

Answer 20

Ask each participant to recommend another possible participant.

Question 21

Quota sampling

Answer 21

Samples from the population non-randomly until you obtain a certain number of participants in identified categories.

Question 22

Key to sampling

Answer 22

It all depends on how the sample was obtained, not how many people are in the sample!!!

Question 23

Types of probability sampling (random)

Answer 23

1. Simple random sample
2. Oversample
3. Systematic sample
4. Cluster/Multistage sample
5. Stratified random sample
   All members of pop of interest have an equal and known chance of being included.

Question 24

Types of non-probability sampling (nonrandom)

Answer 24

1. Convenience sample
2. Purposive sample
3. Quota sample
4. Snowball sample
   Some types of people are systematically left out.