Sampling

Question 1

What is a representative sample?

Answer 1

A sample that accurately represents the population that you are studying.

Question 2

What is a biased sample?

Answer 2

A sample that does not represent the targeted population, contains different characteristics and the procedure favors the selection of certain individuals in comparison to others.

Question 3

Example of biased samples? (3)

Answer 3

1. Researcher going door to door
2. Financial compensation
3. Survey return rate

Question 4

What do we use to calculate minimum sample size?

Answer 4

Power analysis

Question 5

What are the major factors that influence sample size? (4)

Answer 5

1) Size of the difference you need to detect
2) Variability in the factor of interest
3) P value you plan to use as a criterion for statistical significance
4) How confident do you want to be that you will detect statistical significance, assuming a difference exists

Question 6

What is the effect size in the power analysis?

Answer 6

The difference between the mean (quantitative) or proportions (qualitative) of the two groups.

Question 7

What is Standard deviation?

Answer 7

The variability within a sample.

Question 8

What is a Type 1 error?

Answer 8

P level, usually 0.05 (5%).

Question 9

What is power in the power analysis?

Answer 9

The probability of finding an effect (“how confident do you want to be of your effect”), usually 80%.

Question 10

What is the direction of the effect in power analysis?

Answer 10

It can only go up in one tail; up and down in two-tail.

Question 11

What are the types of Statistical tests? (2)

Answer 11

The chi-square, t-test, etc.

Question 12

What is attrition in power analysis?

Answer 12

An adjustment in sample size (eg. death of animals, dropout)

Question 13

What is the Resource equation?

Answer 13

E = (Total number of animals) − (Total number of groups)

Question 14

What is the E variable? (resource equation)

Answer 14

The degree of freedom of analysis of variance (ANOVA)

Question 15

When do you use the resource equation? (4)

Answer 15

When you cannot predict:
1) Effect size (ie. mean).
2) Standard deviation (ie. no previous findings available).
3) Multiple endpoints measured.
4) Complex statistical procedure used.

Question 16

When do we use non-probability sampling?

Answer 16

When the population is not completely known.

Question 17

What are the two types of non-probability sampling?

Answer 17

1) Convenience sampling
2) Quota sampling

Question 18

What is convenience sampling?

Answer 18

A sampling method where participants are easy/convenient to access/reach and are available to participate.

Question 19

What is quota sampling?

Answer 19

Identify a subgroup, then choose from each subgroup to get a quota.

Question 20

What is simple quota sampling?

Answer 20

Sampling method where little is known about the characteristics of a target population and equal number of participants selected for.

Question 21

What is proportionate quota sampling?

Answer 21

Sampling method where demographics are known and proportionately represented in sample.

Question 22

What is animal research quota sampling?

Answer 22

Sampling method where buying animals from single supplier and thus animals obtained have same proportion on many characteristics.

Question 23

What is the pro of animal research quota sampling?

Answer 23

Provides a sample that is representative of the target population.

Question 24

When do we use probability sampling?

Answer 24

When the target population is know, specifically the size.

Question 25

What are the four probability sampling methods?

Answer 25

1) Simple random
2) Systematic
3) Strata
4) Cluster

Question 26

What is simple random sampling?

Answer 26

Sampling method where all individuals have an equal chance of being selected and each selection is independent of others.
Example: Choose 10 students from this class, give all students a number, then pick 10 numbers.

Question 27

What is simple random sampling with replacement?

Answer 27

After each selection, he/she is added back into the pool and an individual can be chosen more than once.

Question 28

What is the warning (caveat) for simple random sampling?

Answer 28

When participant selection is left completely up to chance, can lead to a sample that is not representative of the population.

Question 29

What is systematic sampling?

Answer 29

Sampling method where you choose every # participant on a list. Combination of simple random sampling + systematic process.

Question 30

What is stratified sampling?

Answer 30

Sampling method where the population is divided into strata (subgroups), then participants selected from each strata.

Question 31

What is simple stratified sampling?

Answer 31

Obtain equal numbers from each strata:
* Equal representation
* Does not represent proportions in the population

Question 32

What is proportional stratified sampling?

Answer 32

Select a different proportion (%) from each strata:
* Proportion depends on what representation in the actual population.
* Difficult to compare between strata if some strata makes up a small percent of the population.

Question 33

Quota vs Simple stratified sampling? Similarities?

Answer 33

Subgroups are grouped together.

Question 34

Quota vs Simple stratified sampling? Differences?

Answer 34

The difference is in random selection
-Quota sampling – not randomly selecting individuals from
the population. Researcher chooses who gets sampled (individuals are pre-selected out of convenience)
-Stratified sampling – randomization first then selection

Question 35

What is cluster sampling?

Answer 35

Sampling method where the population can be identified into clusters; then choose from a proportion of the clusters.

Question 36

Advantage of cluster sampling? (2)

Answer 36

1) Quick and easy to get a large sample
2) Can measure all individuals in groups

Question 37

The disadvantage of cluster sampling?

Answer 37

Some clusters are completely omitted, what if something is unique about certain clusters?