exam review Flashcards
(203 cards)
1
Q
what are the steps of the research process?
A
- choose a research question
- conducting a literature review
- making a hypothesis
- designing the study
- conducting the study
- analyzing the study
- reporting the results
2
Q
3 ways to find a research topic
A
- informal observations
- practical problems
- previous research (most common)
3
Q
informal observations
A
from the world around you, other or own behaviour
4
Q
practical problems
A
seeing an issue and applying research
5
Q
previous research
A
look at journals from areas of interest
6
Q
theory
A
cohesive explanation about a set of events that has not yet been shown to be untrue
- used to explain phenomena
- uses variables
7
Q
hypothesis
A
specific prediction about an event or phenomenon that is testable
- often derived from theories
8
Q
inductive hypothesis
A
many observations for a theory
9
Q
hypothetico-deductive model
A
says that you can get new hypotheses from derived theories
10
Q
what makes a good hypothesis?
A
- it is testifiable and falsifiable
- logical
- positive
- replicable
11
Q
variable
A
a quantity or quality that varies across people or situations
12
Q
quantitative variable
A
a quantity that is typically measured by assigning a number to each individual (height, number of siblings)
13
Q
categorical variable
A
a quality that is typically measured by assigning a category label to each individual (occupation, university major)
14
Q
operational definition
A
a definition of the variable in terms of precisely how it is to be measured
15
Q
population
A
large group of people about whom researchers want to draw conclusions about
16
Q
sample
A
smaller portion or subset of the population that is studied
17
Q
simple random sampling
A
every member of the population has an equal chance of being selected for the sample ( hard to do in practice)
18
Q
convenience sample
A
sample consists of individuals who happen to be nearby and willing to participate (more likely used)
19
Q
independent variable
A
variable manipulated by the experimenter (x)
20
Q
dependent variable
A
variable the experimenter measures (y)
21
Q
extraneous variables
A
any variables other than the IV/DV
22
Q
confounds
A
specific type of extraneous variable that systematically varies with the variables under investigation
23
Q
non-experimental research
A
researcher measures variables as they naturally occur without manipulation
24
Q
what does non-experimental research allow for?
A
description and prediction but NOT for making causal conclusions
25
laboratory study
conducted in the laboratory environment and usually has high internal validity
26
field study
conducted in the real world and usually has high external validity
27
internal validity
the degree to which we can confidently infer a causal relationship between variables
28
external validity
the degree to which we can generalize the findings
29
descriptive statistics
used to summarize the data
30
inferential statistics
used to generalize the results from the sample to the population of interest
31
what are types of descriptive statistics?
measures of central tendency and measures of dispersion
32
measures of dispersion
describes the spread of the scores in a distribution (range and standard deviation)
33
range
the difference between the highest and lowest scores in a distribution
34
standard deviation
a computed measure of how much scores vary around the mean
35
correlation coefficient
a statistical measure of the relationship between two variables
36
when are differences statistically significant?
when calculations indicate that research results are not likely to be result of chance
37
type I error
you rejected the null hypothesis when you should have failed to reject it (false positive)
38
type II error
you failed to reject the null hypothesis when you should have rejected it (false negative)
39
morality
principles set by a group or individual that determine right from wrong
40
ethics
branch of philosophy that questions moral principles and determines the appropriate code of conduct within a field
41
moral principles to consider in scientific research
1. weighing risks against benefits
2. acting responsibly and with integrity
3. seeking justice
4. respecting peoples rights and dignity
42
unavoidable ethical conflict
when something arises you deal with it in a responsible way
43
measurement
the assignment of scores to individuals so that the scores represent some characteristic of the individuals
44
constructs
variables we want to measure that are seemingly not straightforward or simple to measure (personality, attitudes)
45
how do we measure our variables?
must use an operational definition
46
self-report measures
participants report on their own thoughts, feelings and actions
47
behavioural measures
some other aspect of participants behaviour is observed and recorded
48
physiological measures
involve recording any of a wide variety of physiological processes
49
four scales a variable can be measured on
- nominal
- ordinal
- interval
- ratio
50
nominal scale
categorical (qualitative)
51
ordinal scale
rank order, discrete, difference between rank is NOT equal
52
interval scale
numeric scale with NO true zero point and each point is equal distance between each other
53
ratio scale
numeric scale with TRUE ZERO
54
what do the levels of measurement determine?
the type of statistics you can do and conclusions you can make
55
reliability
ability to obtain consistent scores
56
validity
ability of a test to measure what it’s supposed to
57
test-retest reliability
a measure’s consistency over time
58
internal consistency
consistency of people’s responses across the items on a multiple item measure
59
what is used to test internal consistency?
split-half correlation
60
inter-rater reliability
the extent to which different observers are consistent in their judgements
61
how is inter-rarer reliability assessed?
Cronbach’s alpha when judgements are quantitative and Crohen’s Kappa when judgements are categorical
62
face validity
how accurate a measure looks on the surface
63
criterion validity
the extent to which scores on a measure correlate with other variables that one would expect them to be correlated with
64
concurrent validity
criterion is measured at the same time as the construct
65
predictive validity
criterion is measured at some point in the future
66
convergent validity
when new measures are correlated with existing established measures of the same construct
67
content validity
the extent to which your test accurately measures the behaviour you are trying to measure
68
discriminant validity
the extent to which scores on a measure DO NOT correlate with other UNrelated variables
69
socially desirable responding
doing or saying things because they think it is the socially appropriate thing to do
70
demand characteristics
subtle cues that reveal how the researcher expects participants to behave
71
experiment
carefully controlled scientific procedure that manipulates variables to determine cause and effect
72
single factor two-level design
experiments involving a single IV with 2 conditions
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single factor multi-level design
experiments involving a single IV with more than 2 conditions
74
two features of an experiment
1. manipulation of the independent variable
2. control of extraneous variables
75
treatment
any intervention meant to change people’s behaviour for the better
76
treatment condition
the group receiving treatment
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control condition
the group not receiving treatment
78
randomized clinical trial
an experiment that researches the effectiveness of psychotherapies and medical treatments
79
types of control conditions
- no treatment control condition
- placebo control group
- wait list control condition
80
no treatment control conditions
zero treatment (most simplistic)
81
placebo control group
given a placebo
82
wait-list control condition
delayed treatment, they are told they need to wait before receiving treatment
83
between-subjects experiment
- each participant tested only once
- relies on random assignment
84
matched group design
participants are matched on the DV or extraneous variables prior to manipulating the IV
85
within-subjects experiments
each participant tested in all conditions
- order effects and counterbalancing
86
carryover effect
an effect of being tested in one condition on participants behaviour in later conditions
87
practice effect
participants perform a task better in later conditions because they have had a chance to practice it
88
fatigue effect
participants perform a task worse in later conditions because they become tired or bored
89
context effect
being tested in one condition changes how participants perceive stimuli or interpret their task in later conditions
90
order effects
- carryover effect
- practice effect
- fatigue effect
- context effect
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counterbalancing
testing different participants in different orders (does not allow for order to become confounding effect)
92
complete counterbalancing
an equal number of participants complete each possible order of conditions
93
random counterbalancing
the order of the conditions is randomly determined for each participant
94
when is between subject design better?
when you only get one shot
95
when is within subject design better?
if the participant has time and don’t think carryover is an issue
96
mundane realism
when the participants and the situation studied are similar to those that the researcher wants to generalize to and the participants encounter everyday
97
psychological realism
where the same mental process is used in both the laboratory and in the real world
98
construct validity
the research question is clearly operationalized by the study’s methods
99
operationalization
the specification of exactly how the research question will be studied in the experiment design
100
statistical validity
concerns the proper statistical treatment of data and the soundness of the researchers statistical conclusions
101
subject pool
an established group of people who have agreed to be contacted about participating in research studies
102
experimenter expectancy effect
when the experimenter’s expectations about how participants should behave in the experiment affect how the participants behave
103
double blind study
when neither the participant nor the experimenter knows to which condition the participant is assigned
104
manipulation check
separate measure of the construct the researcher is trying to manipulate to confirm that the IV was successfully manipulated
105
pilot test
a small scale study conducted to make sure that a new procedure works as planned
106
when to use non-experimental research?
1. you only have single variable
2. have non-causal relationship between variables
3. there is causal relationship but can not randomly assign participants
4. asking a broad or exploratory question
107
types of non-experimental research
- correlations research (most popular)
- observational research
108
correlational research
measures 2 variables with little or no attempt to control extraneous variables and assesses the relationship between them
109
observational research
researcher makes observations of behaviour in a natural or lab setting without manipulating anything
110
when Pearson’s r can be misleading
when there is restriction of range
111
restriction of range
means that one or both of the variables is truncated and does not vary enough to detect a correlation
112
complex correlational research
involves measuring several variables and assessing the statistical relationships among them
113
factor analysis
a complex statistical technique in which researchers study relationships among a large number of conceptually similar variables
114
regression
statistical technique that allows researchers to predict one variable given another
115
predictor variable (x)
the variables used to make the prediction
116
outcome variable (y)
the variable that is being predicted
117
simple regression
involves using one variable to predict another
118
multiple regression
involves using several variables to predict an outcome variable
119
partial correlation
says correlation between two variables while controlling for others
120
what is qualitative research?
- begins with less focused research question
- collects large amounts of unfiltered data
- describes data using non-statistical methods
121
strengths of quantitative research
- provides precise answers to specific questions
- draws general conclusions about human behaviour
122
weaknesses of quantitative research
- does not give detailed descriptions of behaviour in particular groups or situations
- does not communicate what it’s like to be member of particular group or situation
123
strengths of qualitative research
- helps generate new questions
- detailed descriptions of human behaviour in real world contexts
- can convey what it’s like to be member in particular group or situation
124
weaknesses of qualitative research
- lack of objectivity
- difficult to evaluate statistically
- does not allow for generalization
125
triangulation
use both quantitative and qualitative methods simultaneously to study same general questions and compare the results
126
naturalistic observation
involves observing people’s behaviour in the environment in which it typically occurs
127
disguised naturalistic observation
when researchers make their observations as unobtrusively as possible so that participants are not aware they being studied
128
undisguised naturalistic observation
when the participants are made aware of the researcher presence and monitoring of their behaviour
129
participant observation
researchers become active participants in the group or situation they are studying
130
structured observation
researcher makes careful observations in a particular setting that is more structured
131
coding
clearly defining the set of target behaviours so different observers code them in the same way
132
case study
an in depth and often longitudinal examination of an individual
133
archival research
involves analyzing archival data that have already been collected for some other purpose (may involve content analysis)
134
cross-sectional studies
compare two or more pre-existing groups of people
135
cohort effect
differences between the groups may reflect the generation that people come from rather than a direct effect of age (issue of cross-sectional studies)
136
longitudinal studies
one group of people is followed over time as they age
137
cross-sequential studies
people in different age groups are followed over a smaller period of time
138
survey research
quantitative and qualitative method with two important characteristics:
1. variables are measured using self reports
2. considerable attention is paid to the issue of sampling
139
item-order effect
when the order in which the items are presented affects people’s responses (context effects)
140
open-ended items
simply ask a question and allow participants to answer in whatever way they choose (qualitative)
141
closed-ended items
questionnaire items that ask a question and provide a limited set of response options for participants (quantitative)
142
rating scale
an ordered set of responses that participants must choose from
143
unipolar scales
where only construct is tested (five point scales)
144
bipolar scales
where there is a dichotomous spectrum (seven point scales)
145
BRUSCO model for writing effective items
Brief
Relevant
Unambiguous
Specific
Objective
146
non-probability sampling
occurs when the researcher cannot specify the probability that each member of the population will be selected for the sample
147
convenience sampling
the sample consists of individuals who happen to be easily available and willing to participate in
148
snowball sampling
existing research participants help recruit additional participants for the study
149
quota sampling
subgroups in the sample are recruited to be proportional to those subgroups in the population
150
self selection sampling
individuals choose to take part in the research on their own accord without being approached by researcher directly
151
probability sampling
occurs when the researcher can specify the probability that each member of the population will be selected for sample
152
sampling frame
a list of all the members of the population from which to select the respondents
153
simple random sampling
each individual in the population has an equal probability of being selected for the sample
154
cluster sampling
larger clusters of individuals are randomly sampled and then individuals within each cluster are randomly sampled
155
stratified random sampling
the population is divided into different subgroups and then a random sample is taken from each “stratum”
156
proportionate stratified random sampling
used to select a sample in which the proportion of respondents in each subgroup matches the proportion in the population
157
disproportionate stratified random sampling
used to sample extra respondents from particularly small subgroups
158
sampling bias
occurs when a sample is selected that is not representative of the entire population
159
non-response bias
occurs when there is a systematic difference between survey non-responders from survey responders
160
quasi-experimental research
research that resembles experimental research but is not true experimental research
161
characteristics of quasi-experimental research
an IV is manipulated but it is not possible to include either a control group or random assignment to groups
162
one group design
no control group
163
non-equivalent groups design
no random assignment
164
one group posttest only design
a treatment is given to just one group and an outcome is measured just once
165
one group pretest-posttest design
a treatment is given to just one group and an outcome is measured twice
166
why are control groups so important?
- history
- maturation
- testing
- instrumentation
- regression to mean
- spontaneous remission
167
history
something else happened during the course of the study (9/11)
168
maturation
participants matured or developed over the course of that time
169
testing
measuring the DV at pretest affected responses at posttest
170
instrumentation
the measurement of your device has changed
171
regression to mean
extreme scores tend to normalize to the mean over time
172
spontaneous recovery
things would have improved over time anyway
173
interrupted time series design
measurements are taken in intervals over a period of time (difference is number of pretests and posttests)
174
posttest only nonequivalent groups design
participants in one group are exposed to a treatment, a nonequivalent group is not exposed to the treatment and the two groups are compared
175
pretest-posttest nonequivalent groups design
a treatment group is given a pretest, recieves treatment and is given a posttest
at the same time a nonequivalent control group is given pretest, does not get treatment and is given a posttest
176
interrupted time series design with nonequivalent groups
involves taking a set of measurements at intervals over a period of time both before and after an intervention of interest in two or more nonequivalent groups
177
pretest-posttest design with switching replication
- nonequivalent groups given pretest of the DV
- one group gets treatment and the other doesn’t and the DV is assessed again
- then treatment is added to control group and DV is assessed again
178
switching replication with treatment removal design
the treatment is removed from the first group when it is added to the second group
179
factorial design
experiments that include more than one IV in which each level of one IV is combined with each level of the others to produce all possible combinations
180
between-subjects factorial design
- all factors are between subjects
- no one person recieves both conditions of a factor
181
within-subject factorial design
each subject recieves all conditions
182
mixed factorial design
one factor is between subjects while the other is within subject
183
non-manipulated IV’s
an IV that is measured but is non-manipulated
184
why do you have to be careful when inferring causation from non-experimental studies?
- directionality
- a potential third variable
185
main effects
- the effect of one IV on the DV
- they are independent of each other
186
interactions
when the effect of one IV depends on the level of another
187
three results from factorial designs
- main effect
- interactions
- simple effects
188
spreading interaction
there is an effect of one IV at one level of the other IV and there is either a weak effect or no effect of that IV at the other level of the other IV
189
cross-over interaction
the IV has an effect at both levels but the effects are in opposite directions (most valuable outcome)
190
simple effects
an interaction means that the effects of at least one IV depend on the level of another IV
191
when are simple effects used?
to break down the interaction to figure out precisely what is going on
192
single-subject research
type of quantitative research design involving a small number of subjects
193
single-subject research
type of quantitative research design involving a small number of subjects
194
reasons for single subject designs?
- important to focus intensively on behaviour of individual participants
- important to discover causal relationships
- important to study strong and consistent effects that have biological or social importance
195
social validity
treatments that have substantial effects on important behaviours and can be implemented reliably in the real world
196
steady state strategy
the researcher waits until the participants behaviour in one condition becomes fairly consistent before moving on to the next condition
197
reversal design
- most basic
- researcher measures DV in three phases (baseline, after treatment, return to baseline)
198
multiple treatment reversal design
the baseline phase is followed by separate phases in which different treatments are introduced
199
alternating treatments design
two or more treatments are alternated relatively quickly on a regular schedule
200
problems with reversal design
- if treatment is working it may be unethical to remove
- DV may not return to baseline when treatment is removed
201
multiple baseline design across participants
a baseline is established for each participant and the treatment is then introduced for each one at a different time
202
multiple baseline design across behaviours
multiple baselines are established for the same participant but for different DVs and the treatment is introduced at a different time for each DV
203
multiple baseline design across settings
multiple baselines are established for the same participant but in different settings
