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Intro To Social Science Research Midterm > Midterm > Flashcards

Midterm Flashcards

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1
Q

Issues connected to ethics

A
  • no coercion
  • no persuasions (figure of authority)
  • voluntary participation
  • research should not add risk
  • participants can skip sections in the questionnaire/surveys, refuse to answer all questions during interviews
  • benefits should be provided in any case
  • treating people fairly & with respect
  • discourage people from withdrawing if they decide not to do so
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2
Q

Main Principles in Ethics

A

protect participants from harm

  • research with human participants requires Ethics approval
  • balance between potential harm and benefits of research
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3
Q

Ethics Review Board (ERB)

A
  • usually, universities have two Ethics Review Boards
    1) Full Research Ethics Board
  • they receive greater than minimal risk research, committee of faculty members, REB, community & other members
    2) Delegated REV Review
  • they have minimal risk review, individual will review (REB officers)
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4
Q

Tri-Council Policy Statement Core Principles

A 
concern for human welfare
- means seeking concrete ways to promote the physical and mental wellbeing of participants and protect them from harm
justice
- treat people fairly and equitable
respect for persons
- intrinsic values of human beings
- incorporates dual moral obligation to respect autonomy and protect those who have limited autonomy (vulnerable groups, disabilities, PTSD)
- people should choose freely
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5
Q

Hypothesis

A
  • 2 variables
  • expresses relationships between variables
  • expressed as prediction or expected future outcome
  • logically linked to research question and theory
  • possible to test it to see if it is false or true
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6
Q

null hypothesis

A

no relationship or no effect between variables

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7
Q

alternative hypothesis

A

states that independent variable has an effect on dependent variables

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8
Q

sampling

A

process of selecting observations in research

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9
Q

probability sampling

A

involves random selecting

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10
Q

probability sampling techniques

simple random sampling

A

simple random sampling

  • researcher assigns a single number to each element in the sampling frame without skipping any number in the process
  • a table of random numbers is then used to select elements for the sample

limitations:
- entire list of population should be accessible but not usually the case
- could be quite extensive and expensive
small random sample may not be representative of the population of specific ethnic groups

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11
Q

probability sampling techniques

systematic random sampling

A

systematic random sampling
- design requires a list of certain types of population to be researched
systematically takes every 10th, 20th, element into sample

weakness
- periodicity of people in the list could be done in such a way that sampling will represent only specific gender, race, age, etc.

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12
Q

probability sampling techniques

stratified sampling

A

stratified sampling

  • method for obtaining a greater degree of representativeness
  • it is necessary to divide the population into different subgroups or strata, & then randomly selects final subjects proportionally from the different strata
  • stratification is process of grouping members of a population into relatively homogenous strata before sampling (could be race, gender, age, socioeconomic status)
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13
Q

probability sampling techniques

cluster sampling

A

cluster sampling

  • one of most efficient ways of sampling
  • may be used when not possible to compile a list of all elements that compose the larger population
  • useful when clusters occur naturally such as in schools, universities, hospitals. cluster becomes a unit of analysis and therefore considered a representative of population
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14
Q

non-probability sampling

A

Not random sampling

Selective

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15
Q

non-probability sampling techniques

quota sampling

A

quota sampling

  • gather data from individuals in the same proportion as they are represented in population, (gender, sex, age, race, education)
  • could be face-to-face, email, phone, mail

weakness
- allows research to decide whom to include or not include into study, therefore creates biases

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16
Q

non-probability sampling techniques

reliance on available subjects

A

reliance on available subjects
- accidental sampling, procedure that relies on available subjects

weakness
- findings would represent the opinions only of people with characteristics of those passing the sampling point of specified times

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17
Q

non-probability sampling techniques

purposive/judgemental

A

purposive/judgemental sampling

  • method which researchers used own judgement/knowledge in selecting sample members
  • especially used when research to be conducted among specific sub-groups of people
18
Q

non-probability sampling techniques

snowball sampling

A

snowball sampling

  • term refers to process of accumulation as each located subject suggests other subjects
  • used primarily for exploratory purposes. appropriate when members of the specific population are difficult to find and located in multiple places.
19
Q

Operationalization

A

definition of variable in terms of specific activities to measure or indicate with empirical evidence (i.e., survey questionnaire, method of observing events in a field, etc)
- process of moving from concept to a specific activity or measure that allows research to observe it empirically

20
Q

Conceptualization

A

the process by which concepts are formed through the selective organization of sensory experience
- process of specifying what we mean by a term

21
Q

paradigms

A
  • address philosophical dimensions of social science
  • set of fundamental assumptions and beliefs as to how the world is perceived
  • framework perspective or models from which we see, interpret and understand
22
Q

ontology

A

the view of how we perceive reality

23
Q

epistemology

A

studies knowledge & development of knowledge

24
Q

anxiology

A

branch of philosophy which studies values

- what do we know, what do we values?

25
Q

positivism and post positivism

Paradigms

A
  • both start with testing the theory in form of hypothesis & involve statistical tests in their research process
  • uses qualitative data
26
Q

Interpretivism/Constructivism

Paradigms

A
  • opposite to positivism and post positivism
  • believes knowledge is subjective
  • works with qualitative approach - idiographic approach
27
Q

Pragmatism

Paradigms

A
  • refuses to join debates between interpretivisim and positivism
  • accepts mixture of ontology, epistemology, and axiology
  • uses both qualitative and quantitative to better understand reality
28
Q

Tranformative

Paradigms

A
  • focuses on change and transformation

- participatory and collaborative (work together) - different research approach quantitative or qualitative

29
Q

inductive approach

A
  • form of reasoning that moves from specific cases to general cases
  • aims to develop a theory
30
Q

deductive approach

A
  • form of reasoning that moves from general to specific cases
  • aims to test a theory
31
Q

nomothetic approach

A
  • focuses on numbers and strives to produce general statements
  • quantitative
32
Q

idiographic approach

A
  • specific case

- qualitative

33
Q

Ratio Measures

A

a level of measurement that describes a variable whose attributes have all the qualities of nominal, ordinal, and interval measures and in addition are based on a true zero point

  • most precise, ordered
  • exact value
  • equal intervals
  • natural zero, not arbitrary
    example: weight, height, pulse, blood pressure, time
34
Q

nominal measures

A

Variables whose attributes have only the characteristics of exhaustiveness and mutual exclusiveness.

  • assign numbers to objects where different numbers indicate different objects
  • the numbers have no real meaning other than differentiating between objects
  • no natural order
    example: gender: 1 = 1 female, 2 = male, 3 = other
    race, martial status, religion, type of care, etc
35
Q

ordinal measures

A

variables whose attributes may be logically rank ordered
- assign numbers to object but the numbers have meaningful order/rank
example: socioeconomic status: low, middle, high
size: small, medium large
customer satisfaction: not satisfied, satisfied, very satisfied
patients ranking pain from 1-10

36
Q

interval measures

A

A level of measurement that describes a variable whose attributes are rank ordered and have equal distances between adjacent attributes

  • ordered categories
    distance between value is known
    example: school tests, temperature
37
Q

Scales of Measurement

A

Ratio: Absolute zero
Interval: Distance is meaningful
Ordinal: Attributes can be ordered
Nominal: Attributes are only named: weakest

38
Q

Exploratory Research

A

usually qualitative methods
- could be the first stage of sequence of studies. usually “what” question

example: what factors contribute to - generates a new idea

39
Q

Explanatory Research

A

explains relationships, tests hypothesis’
example: how does salary influence employee satisfaction?

how does ROOM TEMPERATURE influence STUDENT UNDERSTANDING of material during class?
- relationships between variables

40
Q

Descriptive (Description) Research

A

focuses on how, who and what. what is the description of settings

example: what is the current level of employee satisfaction in university
1. provided detail, highly accurate data
2. document causes process or mechanism
3. report on background or context of situation

Intro To Social Science Research Midterm (16 decks)

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