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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.
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. Used when n-cases in a sample are classified into categories or cells - tell us whether the groups are significantly different in size - look at the pattern or distributions - not difference between mean - ex:intro psych class categorized into race -
Bayley Scales of Infant Development
histogram
Content validity
Chi-square test
2. 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)
Analysis of covariance (ANCOVA)
Item analysis (reliability)
Crystallized intelligence
3. Used when equivalent one cannot be isolated
Variability
Nonequivalent control group
Frequency distributions (+variables)
frequency polygon
4. 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
Z-scores
IQ Binet'S equation
Field study
Curvilinear relationship
5. Give descriptive names - No order or relationship among the variables other than to separate them into groups - ex: male-female
Analysis of covariance (ANCOVA)
Item analysis (reliability)
nominal variables
Thematic Apperception Test (TAT)
6. Data that has been counted rather than measured - usually limited to whole or positive values - ex: group size - number of hospital visit - number of symptoms
Discrete data
Correlational relationships
Content validity
Nonequivalent control group
7. Inactive substance or condition disguised as a treatment substance or condition - used to form control group
Item analysis (reliability)
Robert Zajonc
placebo
Aptitude tests
8. The process of representing or analyzing numerical data
Fluid intelligence
statistics
Intelligence
Item analysis (reliability)
9. Subjects alter behaviour because they are being observed
Hawthorne effect
ordinal variables
Lie detector tests
Standard normal distributions
10. figure out how much each score differs (deviates) from the mean by subtracting the mean from each score - square each of these deviation values (to get rid of negative value) - add all these squared deviations to get the sum of square - divide sum by
histogram
Criterion-referenced tests
Descriptive statistics (+types)
variance (calculation)
11. Does not control - but examines how independent variable affects it
dependent variable
Population & related
Reliability (+types)
mode
12. Knowing a fact
Crystallized intelligence
Statistical regression
Aptitude tests
Wechsler Adult Intelligence Scale (WAIS)
13. Overall range or spread - most basic measure of variability - subtracts the lowest value from the highest value in a data set
Graphs (types)
range
Statistical regression
Meta-analysis
14. How stable measure is; test-retest - split-half
dependent variable
Selective attrition
Reliability (+types)
interval variables
15. Combines longitudinal and cross-sectional approach
cohort-sequential design
Two-way ANOVA
random sampling
Projective tests (+types)
16. Number of SD a score is from the mean - For normal distribution - (-3 to +3)
percentiles
ordinal variables
Lie detector tests
Z-scores
17. Tests the same person at multiple time points and looks at changes within that person
Achievement tests
placebo effect
within subject
Discrete data
18. Neither purely descriptive nor purely inferential - can only show relationship - not causality - positive and negative correlation
Correlational relationships
Type I and II errors
Objective tests (+types)
Cross validation
19. Measure the extent to which test measures what it intends to; concurrent - construct - content - face
frequency polygon
Z-scores
External validity (+types)
Correlational relationships
20. Neither the subject nor the experimenter know whether the subject is assigned to the treatment or the control group
double-blind experiment
Wechsler Intelligence Scale for Children (WISC-R)
California Personality Inventory (CPI)
External validity (+types)
21. Birth order vs. intelligence; the older - the more intelligent; the more children - the less intelligent; the greater spacing - the more intelligent
Central Tendency (types and distribution differences)
Validity (+types)
Robert Zajonc
Variability
22. 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
nominal variables
Discrete data
Objective tests (+types)
Scientific approach
23. 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
Lie detector tests
independent variable
predictive value
Z-scores
24. Includes: testable hypothesis - reproducible experiment - operationalized definition (observable and measurable)
Content validity
Scientific approach
Mean IQ
Central Tendency (types and distribution differences)
25. Assess extent interests and strengths match those found by professionals in a particular job field
Construct validity
Experimental design
Vocational tests
Achievement tests
26. 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
Spearman r correlation coefficient
F-scale or F-ratio
quasi-experimental design
Scientific approach
27. Frequency polygon (continuous variables) - histogram/ bar graph (discrete)
Beck Depression Inventory (BDI)
Draw-A-Person Test
Graphs (types)
California Personality Inventory (CPI)
28. Has plotted points connected by lines - used to plot variables that are continuous (categories without clear boundaries)
frequency polygon
cohort effect
Wechsler Intelligence Scale for Children (WISC-R)
statistically significant
29. Draw a person of each sex and tell a story about them
Demand characteristic
Beck Depression Inventory (BDI)
California Personality Inventory (CPI)
Draw-A-Person Test
30. Use correlation coefficients in order to predict one variable y from another variable x - let you define a line on graph that describes the relationship between x and y - when the least-square line or regression line is fit to the data - basically: u
independent variable
Linear regression
range
Experimenter bias
31. Takes place in controlled setting must be able to control for: independent variable - dependent variable - and confounding variable
Experimental design
Projective tests (+types)
within subject
double-blind experiment
32. Order - variables need to be arranged by order (not necessarily equally spaced) - ex: maranthon finishers
Population & related
Scientific approach
Wechsler Adult Intelligence Scale (WAIS)
ordinal variables
33. Measure innate ability to learn (debatable) - to predict later performance
Statistical regression
Chi-square test
Aptitude tests
histogram
34. Might show how often different variables appear; nominal - ordinal - interval - ratio (real zero)
Factorial analysis of variance
nominal variables
Frequency distributions (+variables)
Meta-analysis
35. How the score are spread out overall
Variability
ordinal variables
Criterion-referenced tests
Population & related
36. Capable of showing order and pacing because equal spaces lie between the values - do not include real zero - ex: temperature
Correlational relationships
Selective attrition
Content validity
interval variables
37. Whether test items look like they measure the construct
Face validity
Alfred Binet
Z-scores
Content validity
38. Compares 2 groups of people at the same time point
interval variables
Chi-square test
between subject
Graphs (types)
39. 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
normal distribution(+characteristic)
One-way ANOVA
Projective tests (+types)
Bayley Scales of Infant Development
40. Tests whether at least 2 groups co-vary - can adjust for preexisting differences between groups
ratio variables
ANOVA/analysis of variance
Analysis of covariance (ANCOVA)
Type I and II errors
41. 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
Two-way ANOVA
Meta-analysis
John Horn and Raymond Cattell
Mean IQ
42. Measure mastery in a particular area (e.g. final exam)
Criterion-referenced tests
predictive value
statistics
Internal-External Locus of Control Scale
43. 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
Field study
Stanford-Binet Intelligence Scale
Descriptive statistics (+types)
Vocational tests
44. Measure arousal of sympathetic nervous system - stimulated by lying and anxiety
Experimental design
Lie detector tests
Linear regression
Illusory correlation
45. For even number of values in the set - take the average of the two middle value
Nonequivalent control group
Cross validation
Wechsler Adult Intelligence Scale (WAIS)
median
46. Originally to determine mental illness - now for personality; more clinical than CPI; 550 T/F/unsure questions (e.g. 'I would like to ride a horse'); discriminates between disorders; high validity because highly discriminatory items and 3 validity sc
T-score
Minnesota Multiphasic Personality Inventory (MMPI)
Chi-square test
percentiles
47. When subjects act in ways they think experimenter wants or expects
Population & related
percentiles
normal distribution(+characteristic)
Demand characteristic
48. Transformation of a z-score - mean is 50 and the SD is 10 - T=10(Z)+50
cross-sectional design
Continuous data
T-score
Correlational relationships
49. Comparing an individual'S performance on 2 halves of the same test to reveal internal consistency; internal consistency can be increased by item analysis
Scientific approach
Anne Anastasi
Split-half reliability
Robert Zajonc
50. Bell curve; larger the sample - greater chance of having a normal distribution
cross-sectional design
histogram
normal distribution(+characteristic)
Nonequivalent control group