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REC 359 > Final > Flashcards

Final Flashcards

1
Q

What is research?

A

• A systematic process that answers a question and is free from bias

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2
Q

Explain the research process

A
  • Identify research problem
  • Specify research process
  • Collect data, analyze & interpret data
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3
Q

What is a theory?

A

•Unified set of ideas that might explain a question(developed through research)

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4
Q

Inductive vs. Deductive Theory

A
  • Inductive- starts with individual cases, the purpose is to develop overarching theories,(take individual cases build up to theory)
  • Deductive- starts with overarching theories, purpose is to test overarching theories, (start with theory then test it)
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5
Q

What are variables?

A

logical set of attributes

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6
Q

Independent vs. Dependent Variables

A
  • Independent= cause (what you change)

* Dependent= effect (depends on what you change)

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7
Q

What is a Paradigm and why is it important in research?

A

•Framework for how you see the world- it influences what research questions are asked, what results you expect to find, how you collect data

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8
Q

Positivist Paradigm

A

•You believe one truth exists and it can be found using scientific methods (also known as realist)

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9
Q

Post-Positivist Paradigm

A

•There is one truth and it can only be known imperfectly (also realist) *most scientists are this

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10
Q

Constructivist Paradigm

A

•There are multiple truths and each person has own version of reality (therefore own version of truth)

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11
Q

Constructionist Paradigm

A

•Multiple truths w/ own version of reality and everyone’s truth is shaped by social structure (feminist paradigms, race theory) (these ppl. Are critical theorists- knowledge is not value free, critical of truth)

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12
Q

3 purposes of reseach

A
  • Explanation- why?
  • Description- What, where, when, how (usually qualitative)
  • Exploration- learn more about subject, to test feasibility of more extensive study, to develop new methods of collecting and analyzing
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13
Q

Nomothetic

A

•An attempt to identify casual factors of universal “laws”

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14
Q

Correlation vs. Causation

A
  • Correlation- empirical relationship between two variables

* Causation- making/causing something to happen

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15
Q

3 parameters for causation

A

correlation, time order, non-spurious (not coincidental)

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16
Q

Unit of analysis

A

what or whom is being studied

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17
Q

sampling frame

A

•Representation of the pop. you are studying (requires you to consider criteria for who will be included in your study)

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18
Q

Quantitative Research

A

•The numerical representation and manipulation of observed and recorded data describing and explaining phenomena that these observations/data reflect

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19
Q

Pros and Cons of quant. research

A

pros: easy to analyze/summarize
con: can only tell us what happened through numbers

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20
Q

Quant. Methodologies

A
  • Mode- most frequently occurring data point in set
  • Mean- statistical average (add all data points together and divide by number of data points in each set)
  • Medium- middle data point in rank order
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21
Q

Qualitative Research

A

• Collection of empirical materials that describe routine and problematic moments and meanings in individual lives

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22
Q

Pros and Cons of qual. research

A

pros: provides meaning and detail, offers place to start when researchers don’t know what to ask, flexible, cheap
cons: can be interpreted diff. ways, might be superficial (people talking/interacting), data can’t be applied wider

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23
Q

Qual. Methodologies

A

• Mixed Methods- using more than one method to answer question

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24
Q

mixed methods pros and cons

A

pros: address questions at different levels, develop new theories or data collection instrument, overcome weakness of single methodology,
con: takes time, discrepancies in data = challenges

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25
Q

Sequential vs. Concurrent

A

i. Sequential- quant then qual (qual results assist in explaining the findings of a quant study)
ii. Concurrent- two or more methods used to confirm and cross-validate findings (collected at the same time, to strengthen study)

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26
Q

Likert Scale Survey Questions

A

5-7 point scale used to allow individual to rate their attitude about a particular statement (neutral option, equality of scale)

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27
Q

Double Barreled Survey Question

A

• Asking for a single response to a question that has multiple parts

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28
Q

Contingency Questions

A

• Question intended for only some respondents (determined by response to other questions)(relevant, shorter=better, avoid negative items, avoid bias terms)

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29
Q

Survey question order

A
  • Can influence how respondents answer questions
  • Random order = chaotic
  • Most interesting question first- initial question should be non-threatening
  • Dull questions at end
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30
Q

Benefits of Pretesting your Survey

A

• To get out kinks of spelling, wording, question order, clarity of directions

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31
Q

Best practices when conducting surveys

A

• Be familiar with questionnaire, should be similar to pop being studied, follow question wording exactly, record responses exactly *ask probing questions

32
Q

3 Components of ‘No harm to Participants’

A
  • Respect for person- duty to protect sensitive/vulnerable pops. (Children, prisoners, intoxicated ppl.)
  • Beneficence- research should benefit pop. being studied, benefit should be equal to suffering
  • Justice- burdens & benefits of research should be shared fairly w/in society
33
Q

Informed Concent

A

• Norm in which subjects base their voluntary participation in research projects based on a full understanding of the possible risks involved

34
Q

Anonymity

A

• Guaranteed in a research project when participants can’t be identified by either the researchers or anyone else analyzing the data collected

35
Q

Confidentiality

A

• Researchers identify a given person’s responses but promises not to do so publicly

36
Q

Deception

A

• The act of making someone believe something that is not true

37
Q

Debriefing

A

• Way of counter deception- interviewing subjects to learn about their experience of participation in the project & to inform them of any unrevealed

38
Q

What are the obligations of Analysis & Reporting?

A

• Obligation to: Research subjects & scientific community

39
Q

What is IRB? What is its role?

A

• Institutional Review Board- enforce ethical practices and procedures in research especially with human subjects

40
Q

Population vs. Study Population

A
  • Pop: the group we are interested in generalizing about

* Study Pop: the pop from which the sample is actually selected

41
Q

Representativeness

A
  • The quality of the sample in representing the pop you want o generalize about
  • The data derived from the sample should be assumed to represent the pop
  • Enhanced by probability sampling
42
Q

Probability Sampling

A

• The general term for samples selected in accordance with probability theory (random sampling)

43
Q

Random Sampling

A

each element has equal chance of selection

44
Q

Simple Random Sample

A

units composing a pop are assigned numbers, set of random numbers are generated and units have those numbers are included in sample

45
Q

Systematic Sampling

A

every #th unit is selected

46
Q

Cluster Sampling

A

natural clusters are sampled initially, with members of each selected group being sub-sampled afterward

47
Q

Stratification

A

• The grouping of units composing a pop into groups before sampling (can be used in conjunction with other sampling methods to improve representativeness)

48
Q

Non-probability Sampling

A

• Any techniques in which samples are selected in some way not suggested by probability theory

49
Q

4 types of non-probability sampling

A

o Purposeful- units included are selected on bases of researcher’s judgement about which ones will be most useful
o Snowball- each person interviewed may be asked to suggest additional ppl. for interviewing (field research)
o Stratification
o Quota- units selected into sample on pre-specified characteristics so total sample will have same distribution of characteristics assumed to exist in pop.

50
Q

sampling bias

A

• Sampling approach in which some members of the study pop are less likely to be studied than others

51
Q

Validity

A

how accurately the study/data reflects the concept it is intended to measure

52
Q

4 types of validity

A

a. Face Validity- Does the study seem like a reasonable measurement of the variable? (someone unfamiliar with research so it doesn’t make sense to them)
b. Criterion Validity- When conclusion drawn from data set can be compared to criterion data collected later
c. Content Validity-The degree to which a measure covers the range of meanings included within a concept
d. Construct Validity-Degree to which a measure relates to other variables as expected within a system of theoretical relationships

53
Q

Reliability

A

• Quality of measurement methods that suggest the same data would have been collected each time in repeated observations of the same phenomenon

54
Q

Ways to improve Validity

A
  • Triangulation
  • Member checking
  • Inter-coder agreement
  • Memoing (notes to self throughout study)
  • Time sampling
55
Q

Ways to improve Reliability

A
  • Memoing
  • Triangulation
  • Inter-coder reliability
56
Q

Coding

A

identifying important info

57
Q

Qualitative Data Analysis Steps (3 steps)

A
  • Identify important info (coding)
  • Categorize info (developing themes)
  • Recognize Themes (conceptualizing: thoughts become more abstract/big picture, thinking about data as a whole)
58
Q

Direction of Qualitative Data Analysis based on Inductive vs. Deductive Research

A
  • Inductive: individual cases to larger theories

* Deductive: testing theories by looking at individual cases

59
Q

Descriptive coding

A

• Little interpretation to store things known about the data item

60
Q

Analytic coding

A

combining concepts to develop themes

61
Q

Axial Coding

A

• developing themes, relating codes to each other

62
Q

Increasing Validity & Reliability in Qualitative Data Analysis

A

replication of study

63
Q

Univariate Analysis

A

• Analysis of a single variable for descriptive

64
Q

Standard Deviation

A

• the amount of variability in a data set

65
Q

Discrete Variable

A

• Variables whose attributes are separate from one another (gender, race, religion)

66
Q

Continuous Variable

A

• Variable whose attributes form a steady progression (age, income)

67
Q

Bivariate Analysis

A

• Analysis of two variables at once

68
Q

Multi-variate analysis

A

• Analysis of multiple variables at one time

69
Q

Standard Error

A

• Measure of the statistical accuracy of an estimate, the measure of uncertainty (large sample = small error, smaller sample = larger error)

70
Q

Sampling Error

A

• An assumption that the data collected in perfect (error caused by observing a sample and not the entire pop. being studied)

71
Q

Null Hypothesis

A

• Prediction that the two groups we are comparing are not significantly different from one another

72
Q

Alternative Hypothesis

A

• Proposes there is a diff. between two variable being tested

73
Q

Type I Error

A

• When we reject the null hypothesis even though it is true

74
Q

Type II Error

A

• We do not reject null hypothesis, even though it is false

75
Q

T-Test

A

• Analyze two means, comparison of two samples drawn independent of one another

76
Q

P-Values & meaning of being less than .05 or greater than .05

A
  • An obtained significance level
  • Less: null hypothesis is rejected (there is real diff. in variables)
  • Greater: the null hypothesis is retained (no diff. in variables)

REC 359 (1 decks)

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