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Test your basic knowledge |
GRE Psychology: Measurement And Methodology
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Subjects
:
gre
,
psychology
Instructions:
Answer 50 questions in 15 minutes.
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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. Whether test items look like they measure the construct
Face validity
Bayley Scales of Infant Development
Robert Zajonc
Frequency distributions (+variables)
2. When people agree with opposing statements; giving tacit agreement
mental age
Goodenough Draw-A-Man Test
Statistical regression
Acquiescence
3. 31 cards (1 blank and 30 pictures) with interpersonal scenes (2 people facing each other); subject tells story about each which reveals aspects of personality; often measure need for achievement; interpreting terms include needs - press - personology
Robert Zajonc
variance and standard deviation
double-blind experiment
Thematic Apperception Test (TAT)
4. Includes: testable hypothesis - reproducible experiment - operationalized definition (observable and measurable)
Test-retest reliability
Correlational relationships
Meta-analysis
Scientific approach
5. Tell you the average extent to which scores were different from the mean - if average standard deviation is large - then scores were highly dispersed
standard deviation (calculation)
Split-half reliability
median
Pearson r correlation coefficient
6. How much variation there is among n number of scores in a distribution
frequency polygon
Word Association Test
variance and standard deviation
Type I and II errors
7. Order - variables need to be arranged by order (not necessarily equally spaced) - ex: maranthon finishers
Hawthorne effect
ordinal variables
Domain-referenced tests
Robert Zajonc
8. 34.13% - 13.59% - 2.02% - 0.26% and - +3 99.74% - +2 97.72% - +1 84.13% - 0 50.00% - -1 15.87% - -2 2.28% - -3 0.26%
Percentages under normal distribution based on SDs (from mean to end)
Concurrent validity
IQ Binet'S equation
Mean IQ
9. Different subjects of different ages are compared - faster - easier
cross-sectional design
Strong-Campbell Interest Inventory
Null hypothesis
median
10. Not to diagnose depression but assess severity of depressive symptoms; used by researcher or clinician to track course of depressive symptoms
Inferential statistics
Percentages under normal distribution based on SDs (from mean to end)
Bayley Scales of Infant Development
Beck Depression Inventory (BDI)
11. 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
statistically significant
Objective tests (+types)
Meta-analysis
random sampling
12. Tests whether at least 2 groups co-vary - can adjust for preexisting differences between groups
Rosenzweig Picture-Frustration (P-F) Study
within subject
Analysis of covariance (ANCOVA)
Correlational relationships
13. How stable measure is; test-retest - split-half
ordinal variables
Reliability (+types)
nominal variables
Beck Depression Inventory (BDI)
14. Personality test from Jung'S theory; 93 questions 2 answers each; 4-letter personality type - each letter 1 of 2 possible opposing characteristics: Introverted vs. Extraverted - Sensing vs. Intuition - Feeling vs. Thinking - and - Judgment vs. Percep
histogram
Myers-Brigg Type Indicator (MBTI)
Longitudinal design
Rorschach Inkblot Test
15. Used most commonly on standardized test
Domain-referenced tests
percentiles
T-score
Internal-External Locus of Control Scale
16. Organize data by showing it in a meaningful way; do not allow conclusions to be drawn beyond the sample; percentiles - frequency distributions - graphs - measures of central tendency - variability
Julian Rotter
Linear regression
Z-scores
Descriptive statistics (+types)
17. Rosenthal effect; researchers see what they want to see; minimized in double-blind
quasi-experimental design
Experimenter bias
Discrete data
Internal validity
18. Tests the same person at multiple time points and looks at changes within that person
double-blind experiment
Central Tendency (types and distribution differences)
within subject
standard error of mean
19. Tests whether the means on one outcome or dependent variable are significantly different across groups - height or level of anxiety from anxiety scale
Minnesota Multiphasic Personality Inventory (MMPI)
One-way ANOVA
Scientific approach
Hawthorne effect
20. Cartoons in which one person is frustrating another; asked to describe how the frustrated person responds
predictive value
double-blind experiment
Rosenzweig Picture-Frustration (P-F) Study
Empirical-keying or criterion-keying approach
21. The degree to which an independent variable can predict a dependent variable
predictive value
cohort effect
nominal variables
Rosenthal effect
22. Used when equivalent one cannot be isolated
Nonequivalent control group
median
Statistical regression
Q-sort/measure
23. Measure arousal of sympathetic nervous system - stimulated by lying and anxiety
Lie detector tests
Nonequivalent control group
nominal variables
Statistical regression
24. Whether test really taps abstract concept being measured
F-scale or F-ratio
Construct validity
Inferential statistics
One-way ANOVA
25. 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
ordinal variables
Internal-External Locus of Control Scale
F-scale or F-ratio
26. Calculates how off the mean might be in either direction
independent variable
standard error of mean
social desirability
Type I and II errors
27. How a researcher attempts to examine a hypothesis - different questions call for different approaches - some approaches are more scientific than others
within subject
Concurrent validity
research design
Frequency distributions (+variables)
28. Numerically calculating and expressing correlation - r range -1 to +1 - 0 = no relationship
Minnesota Multiphasic Personality Inventory (MMPI)
Pearson r correlation coefficient
generalizability
Reactance
29. Empirical-keying or criterion-keying approach; to determine of subject is like a particular group or not
Linear regression
External validity (+types)
Strong-Campbell Interest Inventory
ordinal variables
30. Critical of personality trait-theory and personality tests; felt situations (not traits) decide actions
California Personality Inventory (CPI)
Walter Mischel
social desirability
cohort-sequential design
31. There is a general factor in intelligence 'g'
statistically significant
Charles Spearmen
Null hypothesis
predictive value
32. Frequency polygon (continuous variables) - histogram/ bar graph (discrete)
Item analysis (reliability)
Graphs (types)
Curvilinear relationship
Charles Spearmen
33. Mean (standard error of mean) - median mode; normal and platykuric: equal; positively skewed: mode - med - mean; negatively skewed: mean - med - mode; bimodal: equal mean and med - 2 modes
ordinal variables
Central Tendency (types and distribution differences)
double-blind experiment
Percentages under normal distribution based on SDs (from mean to end)
34. Measure mastery in a particular area (e.g. final exam)
Criterion-referenced tests
variance (calculation)
Content validity
Rotter Incomplete Sentence Blank
35. Not IQ - It is unlikely IQ captures all facets of it
Intelligence
Strong-Campbell Interest Inventory
Charles Spearmen
Crystallized intelligence
36. Might show how often different variables appear; nominal - ordinal - interval - ratio (real zero)
Minnesota Multiphasic Personality Inventory (MMPI)
Experimental design
Frequency distributions (+variables)
Null hypothesis
37. Interest in the effect of independent variable on the dependent variable - often manipulated by applying it in experimental or treatment condition and withholding it from control condition
between subject
independent variable
T-score
Discrete data
38. Has plotted points connected by lines - used to plot variables that are continuous (categories without clear boundaries)
Curvilinear relationship
range
frequency polygon
placebo effect
39. Similar to word association - finish incomplete sentences
Alpha levels
Lie detector tests
Rotter Incomplete Sentence Blank
Inferential statistics
40. (Mental age/chronological age)/100 - Highest age = 16
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41. Neither purely descriptive nor purely inferential - can only show relationship - not causality - positive and negative correlation
Standard normal distributions
Alfred Binet
Correlational relationships
Reactance
42. Revised Binet scale to Stanford-Binet Intelligence Scale; also studied gifted children - those with higher IQs better adjusted
Lewis Terman
Domain-referenced tests
Illusory correlation
Julian Rotter
43. Revised Binet'S version - used with children - organized by age level - Best known predictor of future academic achievement
Word Association Test
Mean IQ
Split-half reliability
Stanford-Binet Intelligence Scale
44. Combines longitudinal and cross-sectional approach
cohort-sequential design
Validity (+types)
range
normal distribution(+characteristic)
45. Whether scores on a new measure correlate with other measures known to test the same construct; cross validation process
Central Tendency (types and distribution differences)
Rosenthal effect
Concurrent validity
quasi-experimental design
46. Number of SD a score is from the mean - For normal distribution - (-3 to +3)
IQ Binet'S equation
Z-scores
Julian Rotter
Experimental design
47. Allow generalization from sample to population - statistics (sample) - parameters (population): use statistics to estimate parameters
Percentages under normal distribution based on SDs (from mean to end)
Anne Anastasi
Inferential statistics
Rosenthal effect
48. For even number of values in the set - take the average of the two middle value
Criterion-referenced tests
T-test
Julian Rotter
median
49. Fluid intelligence declines with old age while crystallized intelligence does not
Curvilinear relationship
Linear regression
Central Tendency (types and distribution differences)
John Horn and Raymond Cattell
50. 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
stratified sampling
Vocational tests
social desirability
quasi-experimental design
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