Statistics: Population and Sampling

Study Notes

Population: the entire group under study as defined by research objectives
Census: requires information from everyone within a population instead of a sample
Sample: a subset of the population that should represent the entire group
Sample Unit: the basic level of investigation
Sample Frame: a master source of sample units in the population
Sampling Frame Error: the degree to which the sample frame fails to account for all of the population
Sampling Error: any error in a survey that occurs because a sample was used

Members of the population have a known chance (probability) of being in the sample
Types:
- Simple Random Sampling
- Systematic Sampling
- Cluster Sampling
- Stratified Sampling

The probability of being selected into the sample is equal for all members
Probability of selection = sample size / population size
Methods:
- Random Device Method
- Blind draw
- Random number
- Random digit dialing (RDD)

An efficient method of selecting a random sample from a directory or list
Uses a skip interval for selection (selects every other qualified member for the sample)

The population is divided into subgroups (clusters) that represent the entire population
Area Sampling: divides geographic areas into clusters for sampling
One-step area sample: various geographic areas are similar, so one of these could be representative for all
Two-step area sample: researcher selects a random sample of areas and then decides on an appropriate probability method to sample individuals within the chosen areas

Separates the population into different subgroups (strata) and then samples them all
Used with a skewed population and requires calculating a weighted mean
Types:
- Proportionate Stratified Sample: has sample sizes scaled to population size
- Disproportionate Stratified Sample: sample sizes not scaled to population size, may be more statistically efficient

Not based on fairness, equity, or equal chance
Methods:
- Convenience Sampling
- Chain Referral Sampling
- Purposive Sampling
- Quota Sampling

Samples drawn at the convenience of the interviewer (e.g., Mall interviews)
Sample frame error occurs in the form of members of the population who are infrequent or nonusers

Requires a judgment or an educated guess as to who should represent the population
Subjectivity is introduced, so certain population members have less chance to be selected

Specified percentages of the total sample for various types of individuals to be interviewed
Uses demographics or product use factors; sizes of quota determined by researcher
Ensures convenience samples include desired proportion of different respondent classes

Online Panels: large number of individuals who have agreed to participate in online surveys
River Samples: invites website visitors to take a survey via banners, pop-ups, or other online devices
E-mail List Samples: purchased/procured from a person/firm that has a list of emails of population opt-in members

Define the population
Obtain sample frame
Decide sample method
Decide sample size
Draw the sample
Validate the sample (inspect characteristics of respondents to see if it matches with population characteristics)