chapter 7 Flashcards
(37 cards)
1
Q
regression analysis
A
- examine the relationship between a dependent variable and one or more independent variables
- calculates a single correlational values and compares to the outcome variables
- looks at how well the other variables predict that specific outcome
2
Q
predictor variable
A
variable that is used to make the prediction
3
Q
outcome/criterion variable
A
the variable that is being predicted
4
Q
regression
A
- a statistical technique that allows researchers to predict one
variable given another - regression can also be used to describe more complex relationships between more
than two variables
5
Q
simple regression
A
using one variable to predict another
6
Q
multiple regression
A
- involves measuring several variables (X1, X2, etc), and using them to predict some outcome variable (Y)
- can also be used to simply describe the relationship between a single outcome variable (Y) and a set of predictor variables (X1, X2, etc)
7
Q
weakness of regression analysis
A
fails to look at how things relate to each other by looking at them individually
8
Q
quantitative research
A
start with a focused research question or hypothesis, collect a small amount of numerical data from a large number of individuals, describe the resulting data using statistical techniques, and draw general conclusions about some large population
9
Q
qualitative research
A
- doesn’t involve numerical values but data that is non-numerical such as words/interviews and photos
- understanding experience at a much deeper level then just attempting to calculate a numerical value through peoples perceptions and perspectives
- helps identify important variables and generates new ideas
- create or improve quantitative measures through focus groups, interviews, expert input
10
Q
qualitative traditions
A
- ways qualitative research has traditionally been done and also the types of qualitative study:
- ethnography
- phenomenology
- field research
- grounded theory
11
Q
ethnography
A
- studying a phenomenon in the context of its culture or subculture
- e.g. compare impact of varying culture of having an experience
- e.g. used this approach for truth and reconciliation but discussing the historical and current events impacting Indigenous culture and then analyzed the statements to extract data
- e.g. analyzing gaming subculture on interactions with new gamers to examine the differences between games
12
Q
phenomenology
A
- interested in the individuals experience and understanding the experience and its meaning
- in‐depth interviews is the predominant research method
- identifying “Meaning Units” as data analysis and apply them from one interview to another to identify common themes
- e.g. how is giving birth experiences by first time mothers
13
Q
field research
A
- researcher goes into the field to observe the phenomenon in its natural state; go to where the experience is happening
- a method used in other types of research (ethnography or phenomenology)
- qualitative data can have very creative research based on data such as texts, social media, photos, etc
14
Q
grounded theory
A
- Goal is to build a theory grounded in reality and based on data gathered
- rooted in observation about phenomena of interest
- a grounded theory is causative
15
Q
assessing qualitative research
A
- should be able to calculate as much of the following as you can:
1. credibility
2. transferability
3. dependability
4. confirmability
16
Q
credibility/validity in qualitative research
A
- credibility of data is how accurately are you reflecting the experience you are attempting to reflect
- bringing data back to participants to ensure data/information extracted accurately reflect the experience
17
Q
transferability in qualitative research
A
- generalizability, applicability and transferability across groups
- e.g. grief group in edmonton vs. grief group in calgary vs. people grieving not in grief group
18
Q
dependability in qualitative research
A
- reliability over time
- describe the experience no matter where you are in the experience (beginning vs. end)
19
Q
confirmability in qualitative research
A
- replicability, can the study be repeated
- determined by taking data and having someone else, like another researcher, analyze it
20
Q
thematic analysis in qualitative research
A
- identify, analyze, and interpret recurring patterns or themes within a dataset, such as interviews or transcripts, to understand different subjects and interpretations
- finding themes in pages of verbal interview from research participants
- time intensive
21
Q
non-experimental research
A
- research that lacks the manipulation of an independent variable
- simply measures variables as they naturally occur in the lab or real-world
22
Q
when to use non-experimental research
A
- the research question or hypothesis relates to a single variable rather than a statistical relationship
between two variables - the research question pertains to a non-causal statistical relationship between variables
- the research question is about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions for
practical or ethical reasons - the research question is broad and exploratory, or is about what it is like to have a particular
experience
23
Q
types of non-experimental research
A
- correlational research
- observational research
24
Q
correlational research
A
the researcher measures two variables with little or no attempt to control
extraneous variables and then assesses the relationship between them
25
observational research
- focuses on making observations of behavior in
a natural or laboratory setting without manipulating anything
- e.g. milgrams obedience study
26
cross-sectional studies
- involve comparing two or more pre-existing groups of people
- no manipulation of an independent variable and no random assignment of participants to groups
- e.g. children at different stages of development
27
cross-sequential studies
- combines elements of both cross-sectional and longitudinal studies
- researchers adopting this approach choose a smaller period of time during which they follow people in different age groups
28
restriction of range
when one or both of
the variables have a limited range in the sample relative to the population
29
directionality problem
X causes Y or
because Y causes X
30
third-variable problem
- X and Y, can
be statistically related not because X causes Y, or because Y causes X, but because some third variable, Z,
causes both X and Y
- correlations that are a result of a
third-variable are often referred to as spurious correlations
31
factor analysis
- organizes the variables
into a smaller number of clusters
- each cluster is then interpreted as multiple measures of the same underlying
construct
- however factors are not categories, and factor analysis reveals only the underlying structure of the
variables
32
naturalistic observation
observational method that involves observing people’s behavior in the
environment in which it typically occurs making it a form of field research
33
disguised naturalistic observation
naturalistic observation usually make their observations as unobtrusively as possible so that participants are not aware that they are being
studied
34
reactivity
- when a measure changes participants’ behaviour
- when people know they are being observed and studied, they may act differently than they normally would also called the hawthorne effect
35
participant observation
- researchers become active participants in the group or situation they are
studying
- there may be important information that is only accessible to, or can be interpreted only by, someone
who is an active participant in the group or situation
36
disguised participant observation
the researchers pretend to be members of the social group they are observing and conceal their true identity as researchers
37
structured observation
- the investigator makes careful observations
of one or more specific behaviours in a particular setting that is more structured than the settings used in naturalistic or participant observation
- often not the natural setting but lab environment
- gathering quantitative rather than qualitative data
