Chapter 2

Question 1

Equal probability selection method (EPSEM)

Answer 1

Procedure for producing a sample into which every case in the target population has an equal probability of being selected

Example: picking 100 RANDOM students out of 1000 to avoid biases

Question 2

Hypothetical construct

Answer 2

A phenomenon or construct assumed to exist, and used to explain observed effects, but as yet unconfirmed; stays as an explanation of effects while evidence supports it.

Example: Intelligence

Question 3

Mixed methods

Answer 3

An approach which combines both quantitative and qualitative methods as part processes in a single research process

Example: survey + interview

Question 4

Operational definition

Answer 4

Definition of a phenomenon in terms of the precise procedure taken to measure it

Example: measure happiness on a scale from 1-7

Question 5

Participant variables

Answer 5

Person variables (e.g., memory ability) differing in proportion across different experimental groups, and possibly confounding results

Example: age, ethnicity, gender etc..

Question 6

Population

Answer 6

All possible members of a category from which a sample is drawn.

Example: , if you are conducting a study on the academic performance of all high school students in a particular city, the population would include every high school student in that city, which could be thousands of students. (not practical, but makes the point)

Question 7

Positivism

Answer 7

Methodological belief that the world’s phenomena, including human experience and social behavior, are reducible to observable facts and the mathematical relationship between them. Includes the belief that the only phenomena relevant to science are those that can be measured.

“Example”: Empirical + measure/math

Question 8

Qualitative approach

Answer 8

Methological stance in gathering qualitative data which usually holds that information about human events and experiences, if reduced to numerical form, loses most of its important meaning for research.

Example: interviews

Question 9

Qualitative data

Answer 9

Information gathered that is not in numerical form

Question 10

Quantitative data

Answer 10

Information about a phenomenon in numerical form, i.e., counts or measurements.

Question 10

Quantitative approach

Answer 10

Methodological stance gathering quantitative data following a belief that science requires accurate measurement and quantitative data

Example: survey

Question 11

Random number

Answer 11

Number not predictable from those preceding it

Question 11

Randomise

Answer 11

To put the trials of, or stimuli used in, an experiment into an unbiased sequence, where prediction of the next item is impossible

Question 11

Randomly allocate

Answer 11

To put people into different conditions of an experiment on a random basis

Question 12

Reification

Answer 12

Tendency to treat abstract concepts as real entities.

Example: “we need to find justice”

Question 13

Reliability

Answer 13

Extent to which findings or measurements can be repeated with similar results; consistency of measures

Question 14

Sample

Answer 14

Group selected from population of an investigation

Example:

Question 15

Biased (sample)

Answer 15

Sample in which members of a sub-group of the target population are over-or under-represented

Example: sending out a political survey to only the rich neighbourhoods

Question 16

Cluster (sample)

Answer 16

Groups in the population selected at random from among other similar groups and assumed to be representative of a population

Example: instead of studying the reading habits of all 20 schools in the city, you randomly pick 5 .

Question 17

Convenience/Opportunity (sample)

Answer 17

Sample selected because they are easily available for testing

Example: just getting whoever stops at your stand to complete the survey

Question 18

Haphazard (sample)

Answer 18

Sample selected from population with no conscious bias (but likely to be truly random)
- Related to Convenience/Opportunity

Example:

Question 19

Opportunity (sample)

Answer 19

See convenience

“Sample selected because they are easily available for testing”

Question 20

Purposive (sample)

Answer 20

Non-random sampling of individuals likely to be able to make a significant contribution to the data collection for a qualitative project either because of their specific experience or because of their expertise on a topic

Example: conducting a study on the experiences of war-veterans suffering from PTSD, and only selecting people who have or have had PTSD for the study

Question 21

Quota (sample)

Answer 21

Sample selected, not randomly, but so that specific groups will appear in numbers proportional to their size in the target population

Example: you want 50% men and 50% woman for a specific study

Question 22

Representative (sample)

Answer 22

Type of sample aimed at if results of the research are to be generalized; it is hoped that the sample will contain sub-groups of people in direct proportion to their prevalence in the general population.

Example: Diversity, Random selection, sample size, and data collection (gathering valuable and relevant data)

Question 23

Self-selecting (sample)

Answer 23

The sample selected for study on the basis of members’ own actions in arriving at the sampling point

Example: students decide themselves if they want to participate in the study

Question 24

Simple random (sample)

Answer 24

sample selected in which every member of the target population has an equal chance of being selected and all possible combinations can be drawn

Example: random valg i fotball på skolen (tall 1-13)

Question 25

Stratified (sample)

Answer 25

Sample selected so that specific sub-groups will appear in numbers proportional to their size in the target population; within each sub-group cases are randomly selected.

Example: Percentage and not number

Question 26

Systematic random (sample)

Answer 26

Sample selected by taking every nth case from a list of the target population; “random” if starting point for n is selected at random.

Example: 100 customers, each get a number. Randomly start at 36 and then every 10 after that.

Question 27

Sampling bias (or selection bias)

Answer 27

Systematic tendency toward over-or under-representation of some categories in a sample.

Example: basically not picking a representative sample

Question 28

Sampling frame

Answer 28

The specified range of people from whom a sample will be drawn. Those within a population who can be sampled.

Example: 100 students. Only going to sample 10. Sampling frame = 100

Question 29

Target population (sample)

Answer 29

Similar to the sampling frame but more theoretical. The assumed population of people from which a sample is to be drawn. Very often the aim is to be able to generalize sample results to this population.

Example: conducting a study on job satisfaction in a company. The entire company is the target population

Question 30

Validity (sample)

Answer 30

The extent to which instruments measure what they are intended to measure. Also, the extent to which a research effect can be trusted as real or as not, “contaminated” or confounded.

Example:

Question 31

Variable (sample)

Answer 31

Phenomenon that varies. In psychology usually refers to a phenomenon for which an objective measure has been provided.