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PSY 301 RMA > 2017-09-21 01 Exam > Flashcards

2017-09-21 01 Exam Flashcards

1
Q

primary research article

A

(A & L, 32)

- author(s) report original research they conducted

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2
Q

steps in the research process

A

(A & L, 11-25)
Aka the scientific method
1) identify your topic: interests you and others based on an established opinion/belief, no special/specific participants, have q’s but read past research to develop a strong hypothesis/design
2) find, read, and evaluate past research to develop hypothesis/research q: constantly look at past research
3) further refine topic and develop a hypothesis/research q: testable hypothesis
4) choose research design: feasible with resources and time, ethical
5) carry out your study: approval from professor, IRB
6) analyze the data: chose analysis based on hypothesis
7) communicate results: fit/don’t fit with past research, limitations

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3
Q

correct format for research article

A

(A & L, 48-58) (in-class 8/31)

1) Abstract
2) Introduction
3) Method
3) a) Participants
3) b) Procedure
3) c) Measures
4) Results
5) Discussion

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4
Q

abstract

A

(A & L, 51) (in-class 8/31)

  • 150-200 words
  • like a movie trailer (but spoils the end)
  • always first, but created last
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5
Q

introduction

A

(A & L, 53) (in-class 8/31)

  • introduces topic, why it’s important (why people should care)
  • build case for study: describe past research, gaps in it, and limitations (organize broad to narrow)
  • introduce new study, how it’s addressing past limitations/gaps
  • state hypothesis/research questions
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6
Q

method

A

(A & L, 54) (in-class 8/31)

a) Participants
- how many, who are they, consent?, was anyone excluded
b) Procedures
- what did you do step-by-step, data collection process, include anything relevant for replication
c) Measures
- what were key variables?, how were they measured?, example items, scale scoring

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7
Q

results

A

(A & L, 56) (in-class 8/31)
- “just the facts”
- objective description of the results
EX: X correlated with Y

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8
Q

discussion

A

(A & L, 57) (in-class 8/31)

  • restate hypothesis: if findings supported past research, relate to previous research
  • describe limitations
  • why results are interesting/useful
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9
Q

correct APA format and references format

A 
(in-class 8/31)
Dutton, H., & Shen, H. (2017). Title: No more uppercase letters. Just Journal in Italics: 40(5), 223-225. dio:00000
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10
Q

steps to ensure a study is ethical

A

(A & L, 3-11) (in-class 8/29)

  • informed consent: explain study purpose, can withdraw at any time, risks
  • confidentiality: only researchers and participants know defining characteristics (anonymity: only participant knows)
  • incentive: nothing unreasonable (a million dollars)
  • deception: none or ethical
  • debriefing, answering questions: asap after the study
  • approval from IRB
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11
Q

descriptive research design

A

(A & L, 106, 117)

  • Survey
  • Interview
  • Questionnaires
  • Observational
  • Archival
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12
Q

correlational research design

A

(in-class 8/29) (A & L, 20)

  • looks for relationship of 2 observed variables
  • all about causation
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13
Q

experimental research design

A

(A & L, 19)

- determines causal relationship by manipulating IV, measuring DV, and random assignment

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14
Q

independent variable (and levels)

A 
(A & L, 21) (in-class 8/29)
- variable that's manipulated in an experiment
Levels: a control group and then 1 or more other assignments/groups
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15
Q

dependent variables

A

(A & L, ) (in-class 8/29)

  • variable that’s measured in an experiment
  • expected to change based on IV
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16
Q

study reliability and replication

A

(A & L, 69-71, 76) (in-class 9/4)

  • how generalizable is the study?
  • extent to which a set of findings is reproducible
  • does the measure have similar results in many trials
  • are there relatively low levels of measurement error?
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17
Q

internal validity

A

(in-class 9/4, 9/7) (A & L, 71) (in-class 9/4: 351)
- all about causation
- allows researchers to state that they’ve identified causal associations
- was the IV the sole cause of changes in the DV
EX:
- high: well controlled experiment (ideally with random assignment)
- medium: correlational study with statistical controls
- low: did not rule out potential third-variable explanations

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18
Q

scales of measurement

A

(in-class 9/4) (A & L, 79-83)

  • nominal
  • ratio
  • interval
  • ordinal
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19
Q

nominal scale

A

(in-class 9/4) (A & L, 80)

  • identity (each number has a specific meaning)
  • used to measure categories
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20
Q

ratio scale

A

(in-class 9/4) (A & L, 80)

  • identity (each number has a specific meaning), order (numbers on a scale, in ordered sequence), equal intervals (distance between numbers on the scale is equal), true zero (fixed-point)
  • used to measure quantities
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21
Q

interval scale

A

(in-class 9/4) (A & L, 80)

  • identity (each number has a specific meaning), order (numbers on a scale, in ordered sequence), equal intervals (distance between numbers on the scale is equal)
  • used to measure ratings
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22
Q

ordinal scale

A

(in-class 9/4) (A & L, 80)

  • identity (each number has a specific meaning), order (numbers on a scale, in ordered sequence)
  • used to measure rankings
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23
Q

operational definition

A

(in-class 9/4) (A & L, 77)

  • specifics of how the variable is measured
  • so it can be exactly replicated
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24
Q

construct validity

A

(in-class 9/4: 351)
- abstract psychological phenomenon
- inferred from observable behavior
EX: love, attraction, engagement
– need to be specific in how you’re going to measure (unlike a ruler)
- did the authors measure or manipulate ~all facets of the concept~ that they claim to be measuring or manipulating?
- can’t measure directly

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25
Q

measurement validity

A

(A & L, 76)
Measurement is accurate and measure’s what it’s supposed to
- Construct validity (content, divergent, criterion[predictive, concurrent])

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26
Q

content validity

A

(in-prac 9/11) (A & L, 93)
construct validity
- have to measure all aspects of the construct
EX: only measuring one part, but now the full range of what’s being measured

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27
Q

divergent validity

A

(in-prac 9/11) (A & L, 94)
construct validity
- negative or no relationship between 2 scales measuring different constructs
- 2 measures that only really measure one thing

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28
Q

criterion validity

A

(in-prac 9/11) (A & L, 94)
construct validity
- positive correlation between scale scores and a behavioral mesaure

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29
Q

measurement reliability

A 
(in-class 9/4) (A & L, 90)
- internal consistency (Cronbach's Alpha, split-half reliability), test-retest reliability, alternate forms reliability, inter-rater reliability
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30
Q

internal consistency

A

(in-class 9/4) (in-prac 9/11) (A & L, 91)
Consistency of participants responses to all items in a scale
- Cronbach’s Alpha, split-half reliability

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31
Q

Cronbach’s alpha

A

(in-prac 9/11) (A & L, 91)
measures internal consistency
- computes inter-correlations of scale items
- values >0.7 are acceptable internal consistency
- when alpha is <0.7, sometimes items deleted to reach 0.7 standard

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32
Q

split-half reliability

A

(in-prac 9/11) (A & L, )
measurement reliability
- correlations between 2 halves of the items on a scale (ex: even number items correlated with odd-numbered items
- values >0.7 are considered acceptable reliability

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33
Q

test-retest reliability

A

(in-class 9/7) (in-prac 9/11) (A & L, 91)
measurement reliability
- check again if the measurement could be unstable
- same question, different answer (means question is picking up something else)

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34
Q

interrater reliability

A

(in-class 9/7) (in-prac 9/11) (A & L, 91)
measurement reliability
- for when people are being observed, field work with complicated behaviors (not relevant for survey data [questionnaire])
- multiple people coding

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35
Q

3 criteria of an experiment

A

(A & L, 19)

1) random assignment
2) manipulation of IV
3) measurement of DV

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36
Q

descriptive study

A

(A & L, 19)

- describe variables, but don’t examine relationship or causation

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37
Q

Survey research

A

(A & L, 106)
Descriptive research design
- interviews or questionnaires where participants report attitudes or behaviors
- Advantages: insight into how participants see themselves, can be administered easily (online, a lot at a time)
- Disadvantages: social desirability bias, interviews time consuming, interviewer bias, questionnaire don’t get as much in depth info

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38
Q

interview

A

(A & L, 106, 117)
Descriptive research design, survey
- 1-1 conversations directed by researcher
- phone, in person, email
- can’t be anonymous, but can be confidential

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39
Q

questionaire

A

(A & L, 85, 108, 117)
Descriptive research design, survey
type of measurement
- allow for anonymity (reduce social desirability bias)
- can be administered easily (online, a lot at a time)
- asses one or more construct

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40
Q

observational study

A

(A & L, 109)
Descriptive research design
- recording behavior
- can be in addition to other research methods
- Advantages: reduce social desirability bias, time consuming to record and code data, potential observer bias)

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41
Q

social desirability bias

A

(A & L, 106)

- in self-reports, people responding in what they thing is the most desirable or ideal

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42
Q

Convert observation

A

(A & L, 111)
Descriptive, observational
- observations made without participants knowing
- to capture participants natural and spontaneous reactions
- can be unethical (can be in a public place)

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43
Q

overt observation

A

(A & L, 111)
Descriptive, observational
- no attempts made to hide observation
- participants could change behavior if they know they’re being watched
- researchers usually give time for participants to acclimate to situation

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44
Q

naturalistic observation

A

(A & L, 112)
Descriptive, observational
- observations that occur in natural environments/situations
- don’t involve interference by any researcher

45
Q

contrived observation

A

(A & L, 112)
Descriptive, observational
- researcher sets up situation and watches how participants respond
- can be event, physical stimulus, asking participants to complete a task, etc

46
Q

nonparticipant observation

A

(A & L, 112)
Descriptive, observational
- researcher/observer isn’t directly involved in the situation

47
Q

participant observation

A

(A & L, 112)
Descriptive, observational
- researcher/observer is actively involved in the situation

48
Q

external validity

A 
(in-class 9/4: PSY 351)
- ~generalizablilty~ to population of interest (not always everyone)
- are the results true for other: participants? settings? times?
EX:
- high: large, random selection of participants from population of interest; procedure similar to situation of interest
- low: small convenience sample with major differences from population of interest; procedure different frem situation of interest
49
Q

convergent validity

A 
(in-class prac 9/11) (A &amp; L, 93-95)
construct validity
- positive relationship between 2 scales measuring the same or similar items
50
Q

concurrent validity

A

(A & L, 95)
construct validity, criterion validity
- positive correlation between scale scores and a current behaviors that’s related to the assessed construct

51
Q

predictive validity

A

(A & L, 95)
construct validity, criterion validity
- positive relationship between scale scores and future behaviors that’s related to the assessed construct

52
Q

reliability

A 
(in-class 9/7)
- extent a set of findings is reproducable
53
Q

types of measures

A

(A & L, 84-89)

  • Questionnaire
  • response format (open-ended response, closed-ended, forced-choice)
54
Q

response formats

A

(A & L, 86-89)

  • open ended response
  • closed-ended
  • forced choice
55
Q

open-ended response format

A

(A & L, 86-89)

- item on a scale that has respondents generate their own answers

56
Q

closed-ended response format

A

(A & L, 86-89)

- items that have limited number of choices for respondents to choose from (multiple choice)

57
Q

forced-choice response format

A

(A & L, 86-89)
- response format where respondents cannot be neutral (yes/no, true/false)
(nominal)

58
Q

population

A

(A & L, 118)

  • group researchers are interested in
  • defined by specific characteristics
59
Q

subpopulation

A

(A & L, 118)

- portion/subgroup of the population

60
Q

sample

A

(A & L, 119)

- subset of population the data is collected from

61
Q

sampling

A

(A & L, 119)

- process of how the sample is selected

62
Q

sampling bias

A

(A & L, 119)

- when some members of the population are overrepresented

63
Q

probability sampling (random sampling)

A

(A & L, 121)

  • sampling procedure that uses random selection
  • ideal, (external validity/generalizable)
    • simple random, stratified random, cluster sampling
64
Q

random selection

A

(A & L, 121)

- all individual members of a population or sub-population have an equal chance of selection

65
Q

random selection with placement

A

(A & L, 121)

  • selected members of the population are returned to the pool of possible participants
  • any member can be selected into the sample more than once
66
Q

random selection without placement

A

(A & L, 121)

  • selected members of the population are removed to the pool of possible participants
  • member can be selected only once
67
Q

simple random sampling

A

(A & L, 122)
probability sampling
- every member as equal chance of being selected

68
Q

stratified random sampling

A

(A & L, 122)
probability sampling
- key populations are represented based on characteristics (age, gender, ethnicity)

69
Q

cluster sampling

A

(A & L, 122)
probability sampling
- groups (or clusters) are randomly selected, instead of individuals based on categorization (ex: specific schools when target pop is middle schoolers)

70
Q

non-probability sampling (non-random sampling)

A

(A & L, 123)

  • sampling procedure that doesn’t use random selection
    • less time (no need to identify all participants [members, clusters] in a population)
    • if researcher can’t identify all members/clusters, appropriate sample size, and/or minimize non-response data
    • convenience, quota, maximum stratification, snowball,
71
Q

convenience sampling

A

(A & L, 129)
non-probability sampling
- sample is volunteers who are readily available and willing to participate
- typically have an over-represented group
- easiest (feasable)

72
Q

quota sampling

A

(A & L, 130)
non-probability sampling
- results in the sample represent key sub-populations based on characteristics (age, gender, race)

73
Q

maximum variation sampling

A

(A & L, 131)
non-probability sampling
- researcher seeks out full range of extremes in the population

74
Q

snowball sampling

A

(A & L, 132)
non-probability sampling
- participants recruit others into the sample

75
Q

non-response bias

A

(A & L, 122)

- when participants don’t answer all questions, or data differs from participants who did participate

76
Q

descriptive statistics

A

(A & L, 142)

  • used to analyze quantitative and qualitative data
  • quantitative analysis used to summarize characteristics of a sample
    • frequency, percentage
77
Q

frequency

A

(A & L, 143)
descriptive statistic
- how many times a score is in a sample

78
Q

percentage

A

(A & L, 143)
descriptive statistic
- proportion of a score in a sample

79
Q

central tendency

A

(A & L, 147)

  • central score
  • summarizes center of distribution
    • mode, median, mean
80
Q

mode

A

(A & L, 149)
measures central tendency
- most frequent score in a distribution

81
Q

median

A

(A & L, 149)
measures central tendency
- halfway point of distribution

82
Q

mean

A

(A & L, 149)
measures central tendency
- arithmetic average

83
Q

variability

A

(A & L, 150)

  • how much scores are different from each other in a sample
  • observed minimum, observed maximum, range, standard deviation
84
Q

observed minimum

A

(A & L, 150)
measures variability
- lowest score in the sample

85
Q

observed maximum

A

(A & L, 150)
measures variability
- highest score in the sample

86
Q

range

A

(A & L, 150)
measures variability
- distance between observed minimum and maximum

87
Q

standard deviation

A

(A & L, 150)
measures variability
- how much in general the scores in a sample differ from the mean

88
Q

descriptive statistics for nominal data

A

(A & L, 170)

  • frequencies and/or percentages
  • CT: (sometimes mode)
  • variability: –
89
Q

descriptive statistics for ordinal data

A

(A & L, 170)

  • (sometimes: frequencies and/or percentages)
  • CT: median
  • variability: observed min and max
90
Q

descriptive statistics for interval or ratio (normal distribution)

A

(A & L, 170)

  • (sometimes: percentages for each score on an interval scale)
  • CT: mean
  • variability: standard deviation (sometimes: possible min/max for interval, observed min/max for interval and ratio)
91
Q

descriptive statistics for interval or ratio (skewed)

A

(A & L, 170)

  • (sometimes: cumulative percentage)
  • CT: median
  • variability: observed min/max or range
92
Q

archival research

A

(A & L, 113)

  • analysis of existing data/records
  • Advantages: no direct data collection, large time frame, fewer ethical decision, can study some behaviors/attitudes that can’t be obtained through survey/observation
  • Disadvantages: obtaining data, could need to adjust hypothesis, time consuming to collect and code data
93
Q

bar graph

A

(A & L, 158)

  • for nominal or ordinal data
  • y axis: frequency of scores
  • x axis: data or ranks
94
Q

graphing nominal data

A

(A & L, 158)

- bar graph

95
Q

graphing ordinal data

A

(A & L, 158)

- bar graph

96
Q

histogram

A 
(A &amp; L, 161)
- graph showing interval or ratio data
- y axis: frequency of scores
- x axis: interval ratings or ratio scores
(shown like a bar graph)
97
Q

frequency polygon

A

(A & L, 161)
- graph showing interval or ratio data
- y axis: frequency of scores
- x axis: interval ratings or ratio scores
(dots represent points, connected with straight lines, connect to 0 on x axis on both ends)

98
Q

uniform distribution

A

(A & L, 163)

  • non-normal distribution
  • where all scores are the same
99
Q

bimodal distribution

A

(A & L, 163)

  • non-normal distribution
  • has 2 peaks
100
Q

skewed distribution

A

(A & L, 163)

  • non-normal distribution
  • scores on one side with a tail on the other
101
Q

positively skewed distribution

A

(A & L, 163) (in-class 9/14)
- non-normal distribution
- tail on positive side (where it pulls the data), peak on negative side
EX: income, number of sexual partners)

102
Q

negatively skewed distribtion

A

(A & L, 163) (in-class 9/14)
- non-normal distribution
- tail on negative side (where it pulls the data), peak on positive side
EX: number of fingers on adults

103
Q

outliers

A

(A & L, 163)

- responses/observations that are different from the rest of the data

104
Q

validity

A

(in-prac 9/18)

accuracy

105
Q

reliability

A

(in-prac 9/18)

consistency

106
Q

pilot study

A

(in-prac 9/18)

  • still with target population
  • test before spending money
  • work on any possible changes
107
Q

accuracy

A

(in-prac 9/18)

validity

108
Q

consistency

A

(in-prac 9/18)

reliability

PSY 301 RMA (2 decks)

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