Chapter 2 Flashcards
Equal probability selection method (EPSEM)
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
Hypothetical construct
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
Mixed methods
An approach which combines both quantitative and qualitative methods as part processes in a single research process
Example: survey + interview
Operational definition
Definition of a phenomenon in terms of the precise procedure taken to measure it
Example: measure happiness on a scale from 1-7
Participant variables
Person variables (e.g., memory ability) differing in proportion across different experimental groups, and possibly confounding results
Example: age, ethnicity, gender etc..
Population
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)
Positivism
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
Qualitative approach
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
Qualitative data
Information gathered that is not in numerical form
Quantitative data
Information about a phenomenon in numerical form, i.e., counts or measurements.
Quantitative approach
Methodological stance gathering quantitative data following a belief that science requires accurate measurement and quantitative data
Example: survey
Random number
Number not predictable from those preceding it
Randomise
To put the trials of, or stimuli used in, an experiment into an unbiased sequence, where prediction of the next item is impossible
Randomly allocate
To put people into different conditions of an experiment on a random basis
Reification
Tendency to treat abstract concepts as real entities.
Example: “we need to find justice”
Reliability
Extent to which findings or measurements can be repeated with similar results; consistency of measures
Sample
Group selected from population of an investigation
Example:
Biased (sample)
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
Cluster (sample)
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 .
Convenience/Opportunity (sample)
Sample selected because they are easily available for testing
Example: just getting whoever stops at your stand to complete the survey
Haphazard (sample)
Sample selected from population with no conscious bias (but likely to be truly random)
- Related to Convenience/Opportunity
Example:
Opportunity (sample)
See convenience
“Sample selected because they are easily available for testing”
Purposive (sample)
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
Quota (sample)
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
Representative (sample)
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)
Self-selecting (sample)
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
Simple random (sample)
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)
Stratified (sample)
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
Systematic random (sample)
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.
Sampling bias (or selection bias)
Systematic tendency toward over-or under-representation of some categories in a sample.
Example: basically not picking a representative sample
Sampling frame
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
Target population (sample)
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
Validity (sample)
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:
Variable (sample)
Phenomenon that varies. In psychology usually refers to a phenomenon for which an objective measure has been provided.
