PSYC - Ch 5

Question 1

Population

Answer 1

Population - group sharing common characteristics

Target population/population of interest - the group defined by researchers interests

Accessible population - easily available segment of target population, samples are typically selected from this

Question 2

Sample

Answer 2

Sample - subset of the population, ppl selected to participate in the study

Researchers want the sample to be a good/similar representation of the population so that they can generalize the results to the population.

Question 3

Representative Sample

Answer 3

Sample with the same characteristics as the population

All members of the population have an equal or specified chance of being included in the sample

The more representative the sample, the more confidence we have that the results can be generalized to the target population

Question 4

Biased Samples and Sampling Bias

Answer 4

Bias is a major threat to sample representativeness

In a biased sample, the characteristics are different from those in the population ie: older/smarter than the target population

Biased sample results from selection (or sampling) bias - Some members of the target population have a much higher probability of being included in the sample compared to other members

Question 5

Convenience sampling

Answer 5

Biased as you sample only those who are easy to contact

Question 6

Self-Selection/Volunteering Sampling

Answer 6

Biased as you only take those who volunteer

Question 7

Sample Size

Answer 7

A larger sample will be more representative

Law of large numbers - the larger the sample size, the more likely the values are similar to those of the population

Minimum oof 10 participants for statistical purposes

Question 8

Power Analysis

Answer 8

To determine the sample size needed to obtain the expected results with a given degree of confidence

Question 9

Sampling Methods

Answer 9

Probability Sampling
Non-Probability Sampling

Question 10

Probability Sampling

Answer 10

Exact size of the population must be known; must be possible to list all the individuals

Each individual in the population must have a specific (e.g., equal) and known probability of selection

The selection process must be unbiased; must be a random process

Question 11

Non-Probability Sampling

Answer 11

Exact size of the population is NOT known, and it is NOT possible to list all the individuals in the population

The probability each individual has to be selected in the sample is UNKNOWN

The selection process is NOT unbiased; greater risk of producing a biased sample than probability sampling

Question 12

Types of probability Sampling

Answer 12

Simple random sampling
Systematic random sampling
Stratified random sampling
Proportionate Stratified random sampling
Cluster random sampling
Multistage random sampling

Can be unrealistic - lost of time/effort, not practical/possible, need a list of population members

Question 13

Simple random sampling

Answer 13

Each individual has an EQUAL chance of selection

Choice of one individual does not influence the probability of another individual - INDEPENDENT

Sampling with replacement - individual selected is recorded and returned to the population (replaced)

Sampling without replacement - removes each selected individual from the population

ISSUES with simple random sampling - chance determines each selection - possible (though unlikely) to get a distorted sample

Question 14

Systematic Random Sampling

Answer 14

Sample members are selected according to a random starting point and a fixed, periodic interval
- Entire population is enumerated in a list
- Random starting point
- Every nth person

E.g., Select a random sample of 100 participants from a population of 50,000.
Place target population in a list, do 50,000/100 = 500, randomly pick a number from 1 to 500, e.g.,
342, start with 342 and pick every 500th person on the list after that number

Ensures a high degree of representativeness, it may violate the principle of independence

Question 15

Stratified Random Sampling

Answer 15

Population divided into subgroups (strata); equal numbers are then randomly selected from each of the subgroups.

Guarantees that each subgroup will have adequate representation

Ensures all subgroups are equally represented in your sample

Useful when your goal is to make comparisons among subgroups

BUT - does not adequately represent proportions found in population and individuals in the population have different probabilities of being selected

Question 16

Proportionate Stratified Random Sampling

Answer 16

The population is subdivided into strata.
* Number of participants from each stratum is
selected randomly.
* The proportions in the sample correspond to the proportions in the population.
ie: pop - 60% men, 40% women - we choose 60 en and 40 women

Ensures the sample will be representative of the population

Requires a lot of work and may make it difficult or impossible to compare subgroups within strata

Question 17

BCluster Random Sampling

Answer 17

Clusters (preexisting groups) instead of individuals are randomly selected from a list of the population

An easy method for obtaining a large, relatively random sample

BUT selections are not independent (e.g., students in one classroom are more likely to be similar to each other than students in another classroom)

Question 18

Multistage Random Sampling

Answer 18

Random sampling at several stages

Ex: Canadian university professors’ opinions on student literacy
* Stage 1: Randomly select universities across Canada
* Stage 2: Randomly select departments within universities
* Stage 3: Randomly select professors within departments

Effective in choosing a sample that is representative of a widely dispersed population (e.g., political polling)

Cost- and time-effective

But there could be issues with non- independence

Question 19

Types of Non-Probability Sampling

Answer 19

Convenience Sampling
Quota Sampling
Purposive Sampling
Snowball Sampling

Question 20

Convenience Sampling

Answer 20

Participants chosen based on availability and willingness - “first come first served”
ie: man on the street, booth at fair

Easy but weak - sample is probably biased

Less expensive and time consuming than probability sampling methods

To help curb bias, select a reasonably representative sample and clearly describe the selection process

Question 21

Quota Sampling

Answer 21

Subgroups are identified and quotas are established for individuals from each subgroup

Can reflect proportions in population, but not randomly selected

Allows a researcher to control the composition of a convenience sample

Easy, economical, time-efficient but the sample probably is biased

*Reflects proportions in population,
but not randomly selected

Question 22

Purposive Sampling

Answer 22

Known as judgmental, selective, or subjective sampling

Researcher targets a particular group of individuals

E.g.: To study smoking cessation, select only smokers; advertise at tabacco shop, not grocery store

Question 23

Snowball Sampling

Answer 23

Begin with someone who meets the criteria for inclusion in your study
* Then ask them to recommend others who they may know also meet the criteria
* Most used in hard-to-reach populations