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Test your basic knowledge |
GRE Psychology: Measurement And Methodology
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Study First
Subjects
:
gre
,
psychology
Instructions:
Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can
study here
.
Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.
This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.
1. Have order - equal intervals and a real zero ex: age
Anne Anastasi
mode
ratio variables
placebo
2. How the score are spread out overall
between subject
histogram
Variability
Selective attrition
3. Step beyond correlations; allows not only identification of relationship between 2 variables - also make predictions
Longitudinal design
Experimenter bias
Wechsler Adult Intelligence Scale (WAIS)
Statistical regression
4. Attempts to eliminate/minimize these - variables in the environment that might also effect the dependent variable and blue the effect of independent variable on the dependent variable
Word Association Test
Wechsler Intelligence Scale for Children (WISC-R)
cohort effect
confounding variable
5. Allows own answer: expression of conflicts - needs - impulses; content interpreted by administrator - some more objective than others; Rorschach Inkblot Test - Thematic Apperception Test - Rosenzweig Picture-Frustration (P-F) Study - Word Association
Descriptive statistics (+types)
Experimental design
Variability
Projective tests (+types)
6. Measures the extent to which items in a measure 'hang together' and test the same thing
percentiles
Factorial analysis of variance
Minnesota Multiphasic Personality Inventory (MMPI)
Internal validity
7. Not IQ - It is unlikely IQ captures all facets of it
Word Association Test
F-scale or F-ratio
Donald Campbell and Donald Fiske
Intelligence
8. Used when an experiment involves more than one independent variable - can separate the effects of different levels of different variables - can isolate main effects - can identify interaction effects - ex: studying effect of brain lesion on problem s
Concurrent validity
Factorial analysis of variance
Central Tendency (types and distribution differences)
Robert Zajonc
9. Attempt to measure less-defined properties (e.g. intelligence) - check for reliability and validity
Domain-referenced tests
Intelligence
Alpha levels
Objective tests (+types)
10. Developed concept of IQ and first intelligence test (Binet Scale)
Discrete data
Meta-analysis
random sampling
Alfred Binet
11. The approach to construct assessment instruments - involves selection of items that can discriminate between various groups; responses determine if he is like a particular group or not; e.g. Strong-Campbell Interest Inventory
cohort-sequential design
Empirical-keying or criterion-keying approach
dependent variable
Experimenter bias
12. Knowing how to do something
Empirical-keying or criterion-keying approach
Selective attrition
Aptitude tests
Fluid intelligence
13. Originally used with free association techniques; word called out - subject says next word in mind
Word Association Test
normal distribution(+characteristic)
Wechsler Adult Intelligence Scale (WAIS)
Percentages under normal distribution based on SDs (from mean to end)
14. Rosenthal effect; researchers see what they want to see; minimized in double-blind
Experimenter bias
Donald Campbell and Donald Fiske
within subject
Type I and II errors
15. Mean of Americans is standardized to 100 - with SD 15 or 16 depending on test; correlates most with IQ of biological parents and socioeconomic status
Internal validity
Illusory correlation
Mean IQ
Frequency distributions (+variables)
16. Structured - do not allow own answers; more objective than projective tests; not completely objective because most self-reported; Q-sort - Minnesota Multiphasic Personality Inventory (MMPI) - California Personality Inventory (CPI) - Myers-Brigg Type
Walter Mischel
Objective tests (+types)
Null hypothesis
Alfred Binet
17. Consist of vertical bars in which the sides of the vertical bars touch - useful for discrete variables that have clear boundaries - interval variables in which there is some order
median
histogram
Internal-External Locus of Control Scale
generalizability
18. Compares 2 groups of people like an experiment - but this is used when it is not feasible or ethical to use random assignment ex: smoker vs. cancer
quasi-experimental design
mental age
Stanford-Binet Intelligence Scale
Robert Zajonc
19. The degree to which the result from an experiment can be applied to the population and the real world
Construct validity
generalizability
statistics
Projective tests (+types)
20. How a researcher attempts to examine a hypothesis - different questions call for different approaches - some approaches are more scientific than others
Vocational tests
Objective tests (+types)
Robert Zajonc
research design
21. Frequency polygon (continuous variables) - histogram/ bar graph (discrete)
Selective attrition
Continuous data
Domain-referenced tests
Graphs (types)
22. The process of representing or analyzing numerical data
Wechsler Intelligence Scale for Children (WISC-R)
Empirical-keying or criterion-keying approach
Q-sort/measure
statistics
23. Measure arousal of sympathetic nervous system - stimulated by lying and anxiety
Criterion-referenced tests
Lie detector tests
social desirability
Inferential statistics
24. The hypothesis that no real differences or pattern exist
Two-way ANOVA
Hawthorne effect
Null hypothesis
Alfred Binet
25. A level of <0.05or <0.01 means that chance that seemingly significant errors are due to random variation rather than to true systematic variance is less than 5% or 1%
double-blind experiment
John Horn and Raymond Cattell
Reactance
Alpha levels
26. How well a test measures a construct; multitrait-multimethod technique determines validity; internal - external: concurrent - construct - content - face
Cross validation
Validity (+types)
Two-way ANOVA
Robert Zajonc
27. Describe what is seen in each of 10 inkblots; scoring is complex; validity questionable
Crystallized intelligence
independent variable
placebo
Rorschach Inkblot Test
28. Measure mastery in a particular area (e.g. final exam)
Spearman r correlation coefficient
nominal variables
Lie detector tests
Criterion-referenced tests
29. Transformation of a z-score - mean is 50 and the SD is 10 - T=10(Z)+50
T-score
placebo effect
Experimental design
Wechsler Adult Intelligence Scale (WAIS)
30. Not simple and linear - looks like a curved line - ex: arousal and perfomance - high A --> low P - Low A --> low P - medium A --> high P
Curvilinear relationship
Scientific approach
bar graph
Percentages under normal distribution based on SDs (from mean to end)
31. If it is significant - same finding can be generalized to the population - use test of significant to reject null hypothesis
John Horn and Raymond Cattell
Wechsler Intelligence Scale for Children (WISC-R)
Analysis of covariance (ANCOVA)
statistically significant
32. Bell curve; larger the sample - greater chance of having a normal distribution
Projective tests (+types)
normal distribution(+characteristic)
Experimental design
Internal validity
33. Similar to word association - finish incomplete sentences
Rotter Incomplete Sentence Blank
Walter Mischel
interval variables
Mean IQ
34. Sorting cards into a normal distribution; each has a different statement on it about personality; to one end is 'least like self' - other is 'most like self' - and middle is neutral; factor analysis to reduce viewpoints into a few factors
Linear regression
Aptitude tests
Q-sort/measure
Empirical-keying or criterion-keying approach
35. Process in testing concurrent validity
Wechsler Preschool and Primary Scale of Intelligence (WPPSI)
Cross validation
Linear regression
Continuous data
36. Includes: testable hypothesis - reproducible experiment - operationalized definition (observable and measurable)
Criterion-referenced tests
cross-sectional design
Scientific approach
ANOVA/analysis of variance
37. Similar to T-test - but can measure more than 2 groups
placebo
histogram
Projective tests (+types)
ANOVA/analysis of variance
38. Combines longitudinal and cross-sectional approach
Q-sort/measure
cross-sectional design
cohort-sequential design
Word Association Test
39. Fluid intelligence declines with old age while crystallized intelligence does not
standard error of mean
statistically significant
percentiles
John Horn and Raymond Cattell
40. Compares 2 groups of people at the same time point
Reliability (+types)
Walter Mischel
between subject
cohort-sequential design
41. When subject behave differently just because they thing that they have received the treatment substance or condition
Continuous data
placebo effect
dependent variable
Item analysis (reliability)
42. Mathematically combines and summarizes overall effects or findings for a topic; best known for consolidating effectiveness of psychotherapy - can calculate overall effect size or conclusion drawn from a collection of studies; needed when conflicting
Meta-analysis
nominal variables
Concurrent validity
double-blind experiment
43. Used most commonly on standardized test
Charles Spearmen
percentiles
Rorschach Inkblot Test
random sampling
44. compares means of 2 different groups to see if the two groups are truly different - analyze differences between means on continuous data - particularly useful with small n - cannot test for difference between more than 2 groups
Population & related
T-test
Discrete data
F-scale or F-ratio
45. Experimenter bias; researchers see what they want to see; minimized in double-blind
variance (calculation)
Descriptive statistics (+types)
Rosenthal effect
ratio variables
46. Used when equivalent one cannot be isolated
F-scale or F-ratio
Nonequivalent control group
Field study
Crystallized intelligence
47. Tests whether at least 2 groups co-vary - can adjust for preexisting differences between groups
within subject
Learn the shape of different distributions
cross-sectional design
Analysis of covariance (ANCOVA)
48. Empirical-keying or criterion-keying approach; to determine of subject is like a particular group or not
Variability
Robert Zajonc
Meta-analysis
Strong-Campbell Interest Inventory
49. Like a histogram except that the vertical bars do not touch - various columns are separated by space
bar graph
within subject
interval variables
IQ Binet'S equation
50. I when incorrectly reject null - thought significant but chance; II when incorrectly accept null - thought chance but significant
Item analysis (reliability)
Type I and II errors
Alfred Binet
Descriptive statistics (+types)