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MEASUREMENT AND METHOLOGY Flashcards

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1
Q

MEAUREMENT AND METHODOLOGY

A
  • assessment behaviours, attitudesm mental constructs personality, and mental health
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2
Q

Intelligence

A
  • mental construct specifically defined
  • intelligence is NOT IQ
  • IQ is score of inteligence
  • unlikely that IQ captures all intelligence
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3
Q

Alfred Binet

A
  • developed IQ and first IQ test (Binet Scale) = mental age/chronological age x 100
  • Intelligence stops developing after age 16
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4
Q

Mean IQ of Americans

A
  • is 100

- SD = 15 or 16

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5
Q

Stanford Binet Intelligence Scale

A
  • revised version of Binet’s intelligence test

- best known predictor of future academic achievement

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6
Q

Lewis Terman

A
  • from standford university and revised the Binet Intelligence Scale
  • studies of children with higher IQ are better adjusted (gifted children)
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7
Q

Weschler Adult Intelligence Scale (WAIS)

A
  • most commin IQ test for dults

- organized by subtests

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8
Q

Wescler Intelligece Scale for Children (WAIS-R)

A
  • for children age 6-16
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9
Q

Wechsler Preschool and Primary Scale of Intelligence (WPPSI)

A
  • for children age 4-6
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10
Q

Goodenough Draw a Man Test

A
  • notable for cros cultural application an simple directions to draw the very best picture
  • are marked via detial and accuracy, not talent
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11
Q

IQ correlates mostly with who?

A
  • biological parents and socioeconomic status of parents (income or job type)
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12
Q

John Horn and Cattell

A
  • found fluid intelligence decines with old age and cyrstaliized intelignece does not
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13
Q

Robert Zajonc

A
  • relationship between birth order and intelligence
  • firstborns more intellignece than 2nd
  • greater spaces between children = higher intelligence
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14
Q

Charles Spearman

A
  • general factor in human intellignece called “g”
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15
Q

Achievement test

A
  • measure how well you know a particular subject

- measure past learning

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16
Q

Aptitude test

A
  • meaure your innate ability

- predict future perofmrance

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17
Q

Objective test

A
  • subects can’t make own answers, are already structure
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18
Q

Structure test

A
  • more objectively scored than projective tests

- most are self-reported (but still subject to response bias)

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19
Q

Q-sort, Q-measure techniques

A
  • process of sorting cards into normal distrbution
  • each card with a personality statmente and neutral ones and place at the hump and definind or undefining cards are put into the sides
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20
Q

Mineesota Multiphasic personality Inventory (MMPI)

A
  • OG for mental illnes but now a peronality meaure
  • T/F questions
  • items to discriminate between different disorders
  • high validity becau of items and 3 validity scales (lying, carelessness, faking)
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21
Q

California Personality Inventory (CPI)

A
  • use for more “normal” and less clinical groups
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22
Q

Myer-Briggs Type Indicator (MBTI)

A
  • derived from Jung’s personality theory (archetypes)
  • 2 answer per question then given 4 letter personality type
    1) introvert/extravert
    2) sensing/intuition
    3) feeling/thinking
    4) judgment/perception
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23
Q

Julain Rotter

A
  • creater internal/external locus of control
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24
Q

Projective tests

A
  • subjects to create own answer through expression of conflicts, need, impulses
  • content is interpreted by administrators
  • some may be score objectively
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25
Q

Rorschach Inkblot Test

A
  • subject desrcibe what they see in 10 inkblot
  • complex scoring
  • questionable validity
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26
Q

Thematic Apperception Test (TAT)

A
  • cards of interpersonal scences are shown and subject tells story of each card to reveal personality
  • used to measure need for achievmenet
  • needs, press, persnology are terms with test
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27
Q

Reosenweig Picture Frustration (p-F) stud

A
  • cartoons where 1 person is frustrating the other

- subject ask to describe how frustated person responds

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28
Q

Word Association Test

A
  • used in conjucnction with free association tecniques

- word called out, subject says next word that comes to mind

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29
Q

Rotter Incomplete Sentence Blank

A
  • similar to word association

- subject finish sentences

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30
Q

Draw a Person Test

A
  • asks subject to draw a person of each sex and tell a story about them
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31
Q

Beck Depression Inventory (BD)

A
  • not to diagnose depression but for severity of depressive symptoms and track course of symptoms
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32
Q

Empirical-keying or criterion keying approach

A
  • constructing assessment instruments invovles selection of items that discriminate between various groups
  • response determines if person is in particular group or not
  • e.g. Strong-Campbell Interest INventory
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33
Q

Vocational Test

A
  • what extent individual’s interest and strengths match those already found by professionals in particualr job field
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34
Q

Lie detector test

A
  • measure arousal of sympathetic nervous system which becomes stimulated by lying (and anxiety)
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35
Q

walter Mischel

A
  • critical of personality trait-theory and personality tests in general
  • felt situations decided actions (not traits)
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36
Q

Anne Anastasi

A
  • researched intelligence in relation to performance
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37
Q

F-scale or F-ratio

A
  • measurement of facism or authoritarian personality
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38
Q

Bayley Sclaes of Infant Developent

A
  • not intelligene tests
  • mesure senory/motor development of infants to identify mentally retarded children
  • poor predictors of later intelligence
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39
Q

Research design

A
  • how research attempts to examine hypothesis
  • differnt quetions = different approachs
  • some are called more scientific than others
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40
Q

Scientific approach to psychology involves (3)

A

1) testable hypothesis
2) reporductible experiment can be replicated
3) operationalized defintiion of concept under study

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41
Q

Field study

A
  • takes place in naturalistic setting
  • less control over enviornment
  • generates more hpyothesis than can be proved
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42
Q

Experimental design

A
  • takes place in controlled setting

- draw causal conslusions from experiment

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43
Q

IV

A
  • manipulates IV by applying it in experimental or treatment condition by withhodling if from the control condition
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44
Q

DV

A
  • does not control the dependent variable but examineshow IV effects the DV
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45
Q

Confounding variable

A
  • attempts to minimize or eliminate confounds

- variables in environment that might also affect DV and blue effect of IV on DV

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46
Q

Sample or subgroup

A
  • drawn from population bc is impossible to include all members
  • sample must be representative of population and unabiased
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47
Q

Random sampling

A
  • applied to achieve representative population and unbias sample
  • every member of population has an equal chance of getting chosen
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48
Q

Conviencance sampling

A
  • used when random sampling is not possible e.g. a group of psych students
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49
Q

Stratified sampling

A
  • to make results more generalizable then convienanc sampling
  • aims to match emographic characteritcs of sample to demographics of population
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50
Q

Longitudinal design

A
  • studying same objects at differnt points in lifespand and provides better, mored valid result than most other methods
  • time consuming
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51
Q

Cross-sectional design

A
  • different subjects of different ages are compared

- faster, easier than longitudinal

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52
Q

Cohort-sequential design

A
  • combines longiudeninal and cross-sectional approaches
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53
Q

Within-subjects

A
  • test same person at multiple time points and looks at chnges within person
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54
Q

Between-subject design

A
  • compares 2 groups of ppl at the same time point
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55
Q

Quasi-experimental esign

A
  • compares 2 groups of people but design is used when it is not feasible/ethical to use random assignment e.g. you cannot assign one group to smoke for 20 years
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56
Q

Double-blind

A
  • experiments when neither subject nor experimenter knowns whether subject is assigned treatment or control
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57
Q

Placebo

A
  • inactive substance disgused as substance in control group
58
Q

Predicitve value

A
  • degree to which IV can predict DV
59
Q

Generalizability

A
  • degree to which results from experiment can be applied to population and real world
60
Q

Acquiescence

A
  • when ppl agree with opppsing statment

- “careless” responding

61
Q

Cohort effects

A
  • effect that might result when group is born and raised in particular time period
62
Q

Demand characteristic

A
  • subject act in way that they think experimenter wants or expects
63
Q

Experimenter bias

A
  • researchers see what they want to see
  • AKA rosenthal effect
  • minimized in double blind experiment
64
Q

Rosenthal effect AKA

A
  • AKA experimenter bias
65
Q

Hawthorne effect

A
  • subjects alter their behaviour because they know they are being observed
  • applies to workers altering their behaviour for the same reason
66
Q

Nonequivalent control group

A
  • problematic type of control group when an equivalent canot be isolated
67
Q

Placebo effect

A
  • subjects behave different because thy think they have recieved treatment substance or condition
68
Q

Reactance

A
  • attitude change in response to feeeling that options are limited
  • e.g. someone is set on a type of ice cream flavour when they find out it is sold out
69
Q

Selective attrition

A
  • when subjects that drop out of an experiment are different from those that reamin
  • remaining sample is no longer random (morality effects)
70
Q

Social desirability

A
  • when subjects do and say what they think puts them in a favourable light
71
Q

Illusory correlation

A
  • when a relationship is inferred when there is actually is none
  • e.g. people insist a relationship exists between physical and personality characteristics depsite evidence tht no such relationship exits
72
Q

Meta-analysis

A
  • study that mathematically comvines and summarize overall effects of research findings for topic
  • calcualte 1 overall effect size
  • needed when conflicting results are found
73
Q

Insittuional review board (IRB)

A
  • all studies have to pass ethical standards
  • all subjects are provided with risk and benefit of being in study and then sign a consent form
  • Milgram experiment (electric shocks) was the catalyst for higher ethical standards in psychological research
74
Q

Statistics

A
  • process of repreenting or analyzing numerical data
75
Q

Descriptive statistics

A
  • organize data from a sample by showing it in a meaningful way
  • do not allow conclusions to be drawn beyond by the sample
76
Q

Percentiles

A
  • most common on standardized test

- shows position in whole group

77
Q

Frequenecy distrubutions

A
  • how data in study looked

- might show how often different variables appeared

78
Q

Nominal variables

A
  • descriptive bames

- no order or relationship among variables but grouping

79
Q

Ordinal variables

A
  • implies order

- nothing else is known (equal spacing not assumed)

80
Q

Interval variables

A
  • implies order and equal spacing
  • do NOT include a real zero
  • 0 is arbiturary and does not signify absence of temperature
81
Q

Ratio variable

A
  • have order, equal intervals and a real zero e.g. age - incrases by a year, increases and has an absolute 0
82
Q

Graphs

A
  • used to plot zero
83
Q

Frequency polygon

A
  • plotted points connected by lines

- often used to plot continuous varaibles

84
Q

Histogram

A
  • consists of vertical bars in which the sides of vertical bars touch
  • for discrete varisbles that have clear boundaries
  • interval variables where there is order
  • bars lined up in order
85
Q

Bar graph

A
  • vertical lines in historgram but o not touch
86
Q

Measures of central tendecny

A
  • where on a number line the data set falls in general

- 3 types of central tendecny (mean, mode, median)

87
Q

Mean

A
  • average

- affected by high scores (outliers)

88
Q

Standard error of the mean

A
  • calculate how “off” the mean might be in either direction
89
Q

Median

A
  • find the middle of the set
90
Q

Mode

A
  • most frquenctly occuring value
91
Q

Variability

A
  • additional informtion to central tendency by telling you how the scores are spread out overall
92
Q

Range

A
  • basic measure of variability but subtracting lowest to highest value
  • is the spread
93
Q

Variance/standard deviation

A
  • how much variation there is among the number in distrubution
    1) how much each score differs from mean
    2) square each deviation
    3) add all deviations = sum of square
    4) divided by n = variance
    4) take square root of variance = standard deviation
  • large = highly disperesed
94
Q

Normal distribution

A
  • AKA bell curve
  • larger sample = greater chance of bell curve
  • unimodal (one hump) –> mean, median and mode are all equal
95
Q

z-scores

A
  • normal distribution
  • how many standard deviations a score is from the mean
  • usually -3 to 3
96
Q

t-score

A
  • transformation of z-score
  • mean = 50
  • SD = 10
    = t= 10(Z)+50
97
Q

Standard normal distribution

A
  • same thing as normal distribution
  • mean = 0
  • SD = 1
98
Q

Correlations

A
  • part of statistics but neither purely descriptive nor purely inferential
  • show relationships NOT causlity between variables
99
Q

Positive correlation

A
  • simple and linear

- one increases, so does other variable

100
Q

Negative correlation

A
  • simple and liner

- as one variable goes down, the other goes up

101
Q

Cuvilinear correaltion

A
  • not simple and linear

- looks like a curved line e.g. arousal and performance

102
Q

Zero correlation

A
  • no relationship between the variables
103
Q

Person r correlation coefficient

A
  • way of numerically calculating and expressing correlations
  • range from -1 to +1
  • -1 = perfect negative correlation
  • +1 = perfect positive correlation
  • 0 = no relationship
  • strength of relationship is how close it is to -1 or +1
104
Q

Spearman r correlation coefficient

A
  • another correlation and used when the data in form of rank
  • used to determine the line of linear relationships
105
Q

z scores with what percentile rank?

A

34:14:2

106
Q

Regression

A
  • step above simple correaltions

- looks are the variance accounted for

107
Q

Statitical regression

A
  • identify relatioship between 2 variables and makes predictions about 1 variable based on another varible
108
Q

Inferential statistics

A
  • allows generalizability from sample to population
109
Q

Statistics

A
  • numbers that descirbe the sample
110
Q

Parameters

A
  • numbers that describe the popultion
111
Q

Significance

A
  • if numbers that desribe the sample are describing real differences or pattern rather than random variable
  • if significant, research can generalize the same findings to population
112
Q

Test of significance

A
  • hoping to reject the null hypothesis (hypotheis that no real differences exisit)
  • test of significant shows that statiscs were significant and that you can reject the null hypotheis
113
Q

Alpha level

A
  • a significance level used by most of
114
Q

Type 1 error

A
  • incorrectly reject the null hypothesis

- a false positive

115
Q

Type 2 error

A
  • incorrecty accept the null hypothesis

- a flase negative

116
Q

T-tests

A
  • compare means of 2 different groups to see if groups are truely different
  • analyze continuous data
  • can not test for more than 2 groups
117
Q

Chi-square

A
  • when n are classified into categories or cells
  • tells us whether the groups are significantly different in size
  • look at patterns or distributions (not means)
  • analyze categorical or discrete data
  • can assess “goodness of fit” - whether pattern is what would be expected
118
Q

Categorical/discrete data

A
  • data that has been countd rather than measured so limited to positive and whole numbers (usually)
119
Q

ANOVA

A
  • popular because of flexibility

- analyze differences among means of continuous variables but it more flexible because more than 2 groups

120
Q

1 way ANOVA

A
  • tests whether the means on one outcome or DV are significantly diffferent across groups
121
Q

2 way ANOVA

A
  • test the effects of 2 independnet variables or treatment conditions at once
122
Q

Factorial analysis of variance

A
  • used when an experiment involves more than one IV
  • can separate the effects of different levels of different beariables
  • split each IV into levels which yield combinations
123
Q

Main effects (factor analysis)

A
  • the effect of IV on DV
124
Q

Interaction effects (factor analysis)

A
  • combine the IV

- effects of DV change depending on the level of IV

125
Q

Analysis of Covariance (ANCOVA)

A
  • tests whether at least 2 roups co-vary

- can adjust for preexisting differences between groups

126
Q

Linear Regression

A
  • allows use of correlation coefficients in order to predict one variable from another variable
  • meaure relationship but don’t describe the relationship
  • use correlational data to make predictions based on a line fit with the least-squares method
127
Q

Creating tests with statistics

A
  • ensure that measures are on target
128
Q

Standardized test

A
  • used to create norms and tried out on huge groups of people
129
Q

Criterion-reference test

A
  • measure master parituclar subject e.g. final exam
130
Q

Domain-referenced test

A
  • measure less-defined properties e.g. intelligence and need be checked for reliability and validity
131
Q

Reliability

A
  • how stable the measure is
132
Q

Test-re-test reliability

A
  • measured by the same individual taking the same test more than once
  • high test re-test = person would et the same core each time
133
Q

Split-half reliability

A
  • comparing an individuals’ performance on 2 halves of th same test
  • reveals internal consistency of test
134
Q

Item analysis

A
  • increase internal consistency
  • analyze how large group responded to each item on the meaure
  • weeds out problematic items and replaced with better questions with discriminatory value
135
Q

Validity

A
  • how well the test mesures a construct
136
Q

Internal validity

A
  • the extent to which the different items within a measure “hang together” and test the same thing
137
Q

External validity (4)

A
  • extent to which test measure what is intends to measure
    1) concurrent
    2) construct
    3) content
    4) face
138
Q

Concurrent validity

A
  • whether scores on new measure positively correlate with other measures known to test the same construct
  • AKA cross validation
139
Q

Construct validity

A
  • whether the test really taps he abstract concept being measured
140
Q

Content validity

A
  • whether the content of the test covers a good sample of the construct being measured (not just part of it)
141
Q

Face validity

A
  • whether the test items simply look like they measure the construc
142
Q

Campbell & Fiske

A
  • created the multitrait-multimethod technique to determine the validity of test

Psychology GRE (15 decks)

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