Week 4

Question 1

What is standard deviation?

Answer 1

spread form the mean

Question 2

What is positively skewed data?

Answer 2

mean is higher than median

Question 3

What is negatively skewed data?

Answer 3

median is higher than mean

Question 4

What is the null hypothesis?

Answer 4

use of the word ‘no’

Question 5

What is the positive hypothesis?

Answer 5

what you expect the outcome to be

Question 6

What is the theoretical population?

Answer 6

the larger group the researcher wants to generalise findings to

Question 7

What is the study population?

Answer 7

the population the researcher has access to

Question 8

What is a sampling frame?

Answer 8

list of all the participants that usually relates to the study population

Question 9

What is probability sampling?

Answer 9

random selection of participants from a population to ensure that all members of a target population have a chance of being selected

Question 10

What are the pros of probability sampling?

Answer 10

more representative sample with reduced sampling errors and bias

Question 11

What is non-probability sampling?

Answer 11

participants are chosen in a process that does not give all the participants in a population the equal chance of being selected

Question 12

What are the probability sampling techniques?

Answer 12

simple random sampling, systematic random sampling, stratified random sampling, cluster sampling, multistage sampling

Question 13

What are the non-probability sampling techniques?

Answer 13

cluster sampling, snowball sampling, purposive sampling, quota sampling

Question 14

Simple random sampling

Answer 14

*every participant has an equal chance of being selected
+easiest and most common, high generalisability
-not as efficient as stratified random sampling

Question 15

Systematic random sampling

Answer 15

*systematically selected from a list (ie every nth participant)
+easy to use and implement
-systematic biases unless the ordering of participants on the list is random

Question 16

Stratified random sampling

Answer 16

*population divided into groups (strata), then simple random or systematic random sampling is used
+adequate sampling size
-stratas not clearly defined, complicated, time consuming

Question 17

Cluster random sampling

Answer 17

*population randomly divided into a cluster, then a chosen cluster is sampled
+cost effective
-less efficient for large sample sizes

Question 18

Multistage random sampling

Answer 18

*carried out in various stages with a primary population then sub populations
+used when simple random/systematic random/stratified sampling would be too expensive or complex

Question 19

Convenience sampling

Answer 19

*participants are chosen because they are convenient (ie close proximity)
+easy, cost effective, rich qualitative data
-does not produce representative samples, hard to replicate results

Question 20

Snowball sampling

Answer 20

*begin identifying someone who meets criteria and ask them to find other people
+used for hard to reach participants, cost effective
-not used for generalisations, relies on participants to increase sample size, can be saturated

Question 21

Purposive sampling

Answer 21

*look for cases that provide in-depth information about the issue being researched
+can provide the researcher with justifications to make generalisations
-researcher bias

Question 22

Quota sampling

Answer 22

*participants chosen according to pre-specified quotas regarding demographics, attitudes, behaviours etc
+ensures an adequate number of subjects with appropriate characteristics
-not used for generalisations

Question 23

What are the two types of sampling error?

Answer 23

random and systematic - both introduce bias

Question 24

What is random error?

Answer 24

commonly occur in a sample of over- or under- represented groups
can be reduced by increasing sampling size

Question 25

What is systematic error?

Answer 25

cannot be reduced by increasing sampling size, usually occur as a result of inconsistencies or errors in the sampling frame

Question 26

Why is sample size calculated in quantitative research?

Answer 26

to prevent the waste of valuable resources or unethical studies

Question 27

What is the probably of an event that is possible vs impossible?

Answer 27

Impossible = 0
Certain = 1

Question 28

What is a type I (a) error?

Answer 28

probability of detecting a statistically significant effect or difference between study groups in a sample when it does not exist in the target population, false positive

Question 29

If the p value is set at 0.05, what can we say about it?

Answer 29

we can be 95% confident that a real different exists in the population and there is a 5% probability that the findings were due to chance alone

Question 30

What is a type II (b) error?

Answer 30

when the probability of finding that there is no effect or difference between groups in the sample, when in the population, there is a true effect or difference, false negative

Question 31

How can a sample size be calculated?

Answer 31

by using a power analysis

Question 32

What is saturation?

Answer 32

when little or no new data is generated (adequate sample size)

Question 33

Why do sample size for qualitative research tend to be smaller than for quantitative research?

Answer 33

lengthy data collection processes and analysis required for qualitative methods