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Research Methods and Statistics > research ch 3,6,7,8 > Flashcards

research ch 3,6,7,8 Flashcards

1
Q

variable

A

something that varies, must have at least two levels/values

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2
Q

measured variable

A

one whose levels are simply observed and recorded

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3
Q

manipulated variable

A

variable a researcher controls, usually by assigning participants to different levels of that variables

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4
Q

can some variables be both manipulated and measured and example

A

yes, children already in music schools/assign children to music school lessons

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5
Q

constant

A

something that could potentially vary but that has only one level in the study in question

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6
Q

construct variable

A

the name of the concept being studied

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7
Q

conceptual definition

A

a careful, theoretical definition of the construct

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8
Q

operational variable

A

when testing hypotheses with empirical research, also known as operational definition

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9
Q

to operationalize a concept

A

turn it into a measured or manipulated variable

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10
Q

claim

A

an argument someone is trying to make

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11
Q

frequency claim

A

describe a particular rate or degree of a single variable, the variables are always measured and never manipulated

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12
Q

association claims

A

argues that one level of variable is likely to be associated with a particular level of another variable

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13
Q

what does it mean to covary

A

correlate

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14
Q

positive correlation

A

high goes with high, low goes with low

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15
Q

scatterplot

A

a graph in which one variable is plotted on the y-axis and the other one is plotted on the x-axis

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16
Q

negative correlation

A

high goes with low and low goes with high - inverse correlation

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17
Q

zero correlation

A

no association between the variables

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18
Q

verbs for association claims

A

link, associate, correlate, predict, tie to, be at risk for

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19
Q

causal claims

A

argues that one of the variable is response for changing the other

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20
Q

verbs for causal claims

A

cause, enhance, affect, decrease, change

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21
Q

validity

A

appropriateness of a conclusion or decision - claim is reasonable, accurate, and justifiable

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22
Q

construct validity

A

how well a conceptual variable is operationalized

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23
Q

external validity

A

does it generalize

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24
Q

statistical validity/statistical conclusion validity

A

extent to which a study’s statistical conclusions are precise, reasonable, replicable

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25
point estimate
estimate of that value in some population
26
confidence interval/margin of error of the estimate
range designed to include the true population value a high proportion of time
27
three things you have to have for causal claims
covariance, temporal precedence (causal variable comes first) internal validity (third-variable criterion)
28
experiment
one variable is measured, the other is manipulated
29
random assignment
using a method such as rolling a die to decide which participant would follow what level of the study
30
which validity is the priority
external validity isn't always possible, internal is the priority
31
survey vs poll
survey - people asked about a consumer product poll - people asked about their social or political opinions
32
open-ended questions
spontaneous, rich information - drawback is that it must be coded and categorized which is difficult and time consuming
33
forced-choice questions
people give options by picking the best of two or more options
34
likert scale
when a scale contains more than one item and each response value is labelled with the specific terms: strongly agree, agree, neither agree nor disagree, disagree and strongly disagree
35
likest-like scale
it doesn't follow the format exactly
36
semantic differential format
respondents asked to rate a target object using a numeric scale that is anchored with adjectives
37
double-barreled question
asks two question in one, poor construct validity
38
how can question order affect the responses to a survey and what can researchers do about it
white ppl more likely to show support for black rights movements after being asked about women rights - prepare different versions of a survey
39
response sets
types of shortcuts people can take when answering survey questions
40
acquiescence
yea-saying, when people say yes or strongly agree to every item
41
how to fix yea-saying
include reverse-worded items, they slow people down so they answer more carefully
42
fence-sitting
answering in the middle of the scale, especially when survey items are controversial
43
how to fix fence-sitting
take away neutral option (but some people might be neutral) or use forced-choice questions
44
socially desirable responding
when respondents give answers that make them look better than they are
45
how to fix faking good
ensure that the participants know that the responses are anonymous, include target items (my table manners at home are as good as when I eat in a restaurant), ask friend to rate them, use computerized measures to evaluate people's implicit options
46
observational research
when a researcher watches people or animals and systematically records how they behave or what they're doing
47
when is self-reporting impossible
students don't know many words a day they say, mothers can be biased when talking about their children, babies can't report
48
observer bias
when observer's expectations influence their interpretation of the participants' behaviors or the outcome of the study
49
observer effect
observer inadvertently changing the behavior of those they're observing
50
codebooks
precise statements of how the variables are operationalized and the more precise and clear they are the more valid the operationalization will be
51
masked/blind design
observers are unaware of the purpose of the study and the condition to which participants have been assigned
52
reactivity
change in behavior when study participants know another person is watching, might react by being on their best behavior
53
solutions to reactivity
blend in (make unobtrusive observations, one-way mirror ethics), wait it out (habituation), measure the behaviors' results
54
population
the entire set of people or products in which you're interested in
55
sample
a smaller set taken from the population
56
census
the entire population, rarely done
57
population of interest
the one that we want to study
58
biased sample/unrepresentative sample
some members of the population of interest have a much higher probability than others of being included in the sample
59
unbiased sample/representative sample
all members of the population have an equal chance of being included in the sample
60
convenience sampling
using a sample of people who are easy to contact and readily available to participate
61
exit polls
convenience sampling, some people doing the polling find it easier to approach younger people who don't look like they're in a hurry - biased
62
self-selection
when a sample is known to contain only people who volunteer to participate
63
types of representative sampling and explain
simple random sampling (assign a number to each person in the population, select random), systematic sampling (researchers select two random numbers, start with the 4th person in the room and choose every 7th person - time consuming), cluster sampling (cluster of participants random selected and then individuals from there randomly selected - multistage sampling), stratified random sampling (research purposefully select particular demographic categories and then randomly select individuals within each categories - meaningful), oversampling (intentionally overrepresent one or more groups), combining technique
64
types of unrepresentative samples
convenience sampling, purposive sampling, snowball sampling, quota sampling
65
purposive sampling
if researchers want to study only a certain kind of people
66
snowball sampling
participants are asked to recommend a few acquittances for the study
67
quota sampling
the researcher identifies subsets of the population of interest and then sets a target number of each category, non-randomly fills them up
68
bivariate correlation
involves exactly two variables
69
statistical validity in association claims
need to consider the strength and precision of your estimate, if it has been replicated, any outliers, restriction of range, if a seemingly zero association might actually be curvilinear
70
effect size
describes the strength of a relationship between two or more variables
71
confidence interval
95% will contain the true population correlation
72
when is a study statistically significant
when the CI doesn't include zero
73
replication
conducting the study again to find multiple estimates
74
outlier
extreme score, a single case that stands out from the pack
75
restriction of range
if there isn't a full range of scores on one of the variables in the association
76
curvilinear association
the relationship between two variables isn't a straight line, might be positive up to a point and then become negative
77
spurious association
the bivariate correlation is there, but only because of some other third variable

Research Methods and Statistics (2 decks)

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