Quantitative Research Design

Question 1

discerete data

Answer 1

can take only integer values (whole number), no intermediate values

Question 2

discrete scales of measurement

Answer 2

Nominal = participants are grouped into mutually exclusive categories
Ordinal = ranks in order but doesn’t indicate how much better one score is to another (distance between categories is unknown)

Question 3

continuous scales of measurement

Answer 3

Interval = numeric scales, equal units between data points but no true zero.
Ratio = equal units of measurement and an established zero point.

Question 4

what is dv and iv

Answer 4

DV = outcome of interest
IV = variable being manipulated

Question 5

cross sectional approach

Answer 5

Sample of a population
- Descriptive or correlational
- Participants selected from available population of potential relevance to study question
- Rates that result from cross-sectional studies

Question 6

longitudinal approach

Answer 6

• Repeated cross sectional design
  
  • Data collection is conducted on the same target population at each time point.
  • Enables analysing population level changes over time.
  • Cannot assess individual change (as in longitudinal cohort study.

Question 7

cross sectional strengths

Answer 7

• Quick, cheap
  
  • Ethical
  • Data only collected at one time
  • Multiple outcomes and exposures studied
  • Easily genertated hypothesis
    Create in-depth research study

Question 8

cross sectional weaknesses

Answer 8

• Unable to measure incidence
  
  • Difficult to make a causal interference (cause and effect)
  • Difficult to interpret
  • Cannot investigate temporal resolution between outcomes and risk factors
  • Not good for studying rare diseases.
  • Susceptible for biases such as nonresponse bias and recall bias.

Question 9

experimental approach

Answer 9

Used to understand cause-and-effect relationships. Involves comparing 2 or more groups i.e. experimental and control group.

Question 10

quasi experiment

Answer 10

Approximate the conditions of a true experiment, but they don’t control all factors involved
e.g. cannot randomly assign participants to treatment and control groups.

Question 11

single blind trial

Answer 11

= participants do not know whether they are in treatment or control condition.

Question 12

double blind trial

Answer 12

neither participants nor experimenter know who is in which group.

Question 13

between subjects design

Answer 13

different individuals are in each experimental condition basketball players vs volleyball players.

Question 14

within subjects

Answer 14

same individuals do both experimental conditions 2 experimental conditions / multiple time-points.

Question 15

population definition

Answer 15

individuals belonging to the group

Question 16

Probability sampling

Answer 16

individuals belonging to the group

Question 17

non-probability samping

Answer 17

convenience, voluntary, purposive, snowball, quota.

Question 18

sample definition

Answer 18

A selection of people from a given population, i.e. a sample of female elite footballers aged 18-30years

Question 19

other types of sampling

Answer 19

Convenience
Voluntary
Purposive
Snowball
Quota

Question 20

how many participants per group would be enough to provide good analysis according to smith 2022?

Answer 20

20

or for quantitative surveys, 10-20 responses per item per group. (i.e., 20 questions = 100 people; 2 x groups of 20 questions 200 responses)