SUBJECTS
|
BROWSE
|
CAREER CENTER
|
POPULAR
|
JOIN
|
LOGIN
Business Skills
|
Soft Skills
|
Basic Literacy
|
Certifications
About
|
Help
|
Privacy
|
Terms
|
Email
Search
Test your basic knowledge |
GRE Psychology: Measurement And Methodology
Start Test
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. Comparing an individual'S performance on 2 halves of the same test to reveal internal consistency; internal consistency can be increased by item analysis
Crystallized intelligence
Split-half reliability
Domain-referenced tests
Construct validity
2. Not IQ - It is unlikely IQ captures all facets of it
normal distribution(+characteristic)
Intelligence
Standard normal distributions
Minnesota Multiphasic Personality Inventory (MMPI)
3. 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
frequency polygon
standard deviation (calculation)
Descriptive statistics (+types)
variance and standard deviation
4. The degree to which the result from an experiment can be applied to the population and the real world
generalizability
Mean IQ
Continuous data
Stanford-Binet Intelligence Scale
5. 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
Minnesota Multiphasic Personality Inventory (MMPI)
Draw-A-Person Test
Q-sort/measure
Analysis of covariance (ANCOVA)
6. If it is significant - same finding can be generalized to the population - use test of significant to reject null hypothesis
Inferential statistics
Intelligence
statistically significant
Two-way ANOVA
7. Order - variables need to be arranged by order (not necessarily equally spaced) - ex: maranthon finishers
Reliability (+types)
Two-way ANOVA
cohort-sequential design
ordinal variables
8. Studying the same objects at different points in the lifespan and provides better - more valid results than most other methods - costly - time commitment
Variability
Z-scores
Longitudinal design
Meta-analysis
9. Bell curve; larger the sample - greater chance of having a normal distribution
normal distribution(+characteristic)
Linear regression
Standard normal distributions
Item analysis (reliability)
10. Subjects alter behaviour because they are being observed
dependent variable
social desirability
Fluid intelligence
Hawthorne effect
11. Internal-External Locus of Control Scale
Julian Rotter
range
random sampling
standard error of mean
12. 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
quasi-experimental design
standard deviation (calculation)
Walter Mischel
13. Empirical-keying or criterion-keying approach; to determine of subject is like a particular group or not
Content validity
Lie detector tests
Strong-Campbell Interest Inventory
ordinal variables
14. When subjects act in ways they think experimenter wants or expects
Goodenough Draw-A-Man Test
Demand characteristic
nominal variables
Objective tests (+types)
15. Give descriptive names - No order or relationship among the variables other than to separate them into groups - ex: male-female
nominal variables
One-way ANOVA
Internal-External Locus of Control Scale
Thematic Apperception Test (TAT)
16. Does not control - but examines how independent variable affects it
Correlational relationships
dependent variable
Null hypothesis
within subject
17. Not to diagnose depression but assess severity of depressive symptoms; used by researcher or clinician to track course of depressive symptoms
Beck Depression Inventory (BDI)
placebo
Z-scores
Word Association Test
18. Transformation of a z-score - mean is 50 and the SD is 10 - T=10(Z)+50
Aptitude tests
Charles Spearmen
T-score
confounding variable
19. Overall range or spread - most basic measure of variability - subtracts the lowest value from the highest value in a data set
range
mode
research design
Internal-External Locus of Control Scale
20. Birth order vs. intelligence; the older - the more intelligent; the more children - the less intelligent; the greater spacing - the more intelligent
Statistical regression
Acquiescence
statistics
Robert Zajonc
21. Normal curve - negatively skewed distribution - positively sknewed distribution - bimodal distribution - platykuric distribution
statistics
Learn the shape of different distributions
median
Minnesota Multiphasic Personality Inventory (MMPI)
22. How much variation there is among n number of scores in a distribution
Vocational tests
Myers-Brigg Type Indicator (MBTI)
Wechsler Intelligence Scale for Children (WISC-R)
variance and standard deviation
23. How stable measure is; test-retest - split-half
within subject
Validity (+types)
Cross validation
Reliability (+types)
24. Measure the extent to which test measures what it intends to; concurrent - construct - content - face
cohort-sequential design
Nonequivalent control group
Vocational tests
External validity (+types)
25. Combines longitudinal and cross-sectional approach
ordinal variables
cohort-sequential design
Nonequivalent control group
interval variables
26. Similar to word association - finish incomplete sentences
Crystallized intelligence
Rotter Incomplete Sentence Blank
Standard normal distributions
Longitudinal design
27. When subjects do and say what they think puts them in a favorable light -ex: reporting they are not racist even if they really are
Pearson r correlation coefficient
Stanford-Binet Intelligence Scale
social desirability
independent variable
28. Anything that is measured such as height or depression score on a depression scale
Continuous data
Rosenzweig Picture-Frustration (P-F) Study
Population & related
Lewis Terman
29. Used when equivalent one cannot be isolated
range
Nonequivalent control group
Continuous data
Discrete data
30. Naturalistic setting - less control over environment than in lab; generates more hypotheses than able to prove
Field study
Pearson r correlation coefficient
Projective tests (+types)
Strong-Campbell Interest Inventory
31. 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
cohort-sequential design
random sampling
Factorial analysis of variance
Acquiescence
32. Frequency polygon (continuous variables) - histogram/ bar graph (discrete)
Curvilinear relationship
Continuous data
percentiles
Graphs (types)
33. Personality measure for 'normal' / less clinical groups than MMPI - by Harrison Gough
California Personality Inventory (CPI)
Experimental design
Nonequivalent control group
range
34. Revised Binet scale to Stanford-Binet Intelligence Scale; also studied gifted children - those with higher IQs better adjusted
Intelligence
Wechsler Preschool and Primary Scale of Intelligence (WPPSI)
Lewis Terman
Factorial analysis of variance
35. Tests the same person at multiple time points and looks at changes within that person
Continuous data
variance (calculation)
within subject
Bayley Scales of Infant Development
36. Number of SD a score is from the mean - For normal distribution - (-3 to +3)
ordinal variables
Z-scores
Vocational tests
Spearman r correlation coefficient
37. 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%
T-test
predictive value
ratio variables
Percentages under normal distribution based on SDs (from mean to end)
38. Revised Binet'S version - used with children - organized by age level - Best known predictor of future academic achievement
Q-sort/measure
Stanford-Binet Intelligence Scale
Scientific approach
social desirability
39. Neither the subject nor the experimenter know whether the subject is assigned to the treatment or the control group
Goodenough Draw-A-Man Test
standard deviation (calculation)
Selective attrition
double-blind experiment
40. Whether scores on a new measure correlate with other measures known to test the same construct; cross validation process
Stanford-Binet Intelligence Scale
Statistical regression
Linear regression
Concurrent validity
41. Whether test really taps abstract concept being measured
Construct validity
median
Two-way ANOVA
Rorschach Inkblot Test
42. Measure of fascism or authoritarian personality
standard error of mean
F-scale or F-ratio
Julian Rotter
nominal variables
43. Measure innate ability to learn (debatable) - to predict later performance
Percentages under normal distribution based on SDs (from mean to end)
Cross validation
Aptitude tests
Thematic Apperception Test (TAT)
44. 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
Linear regression
Domain-referenced tests
Factorial analysis of variance
Continuous data
45. The hypothesis that no real differences or pattern exist
Rorschach Inkblot Test
within subject
Null hypothesis
Meta-analysis
46. 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
histogram
cohort-sequential design
stratified sampling
Draw-A-Person Test
47. Allow generalization from sample to population - statistics (sample) - parameters (population): use statistics to estimate parameters
Inferential statistics
confounding variable
Spearman r correlation coefficient
Concurrent validity
48. Assess extent interests and strengths match those found by professionals in a particular job field
generalizability
Hawthorne effect
Vocational tests
Descriptive statistics (+types)
49. 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%
Alpha levels
Curvilinear relationship
Stanford-Binet Intelligence Scale
double-blind experiment
50. Created multitrait-multimethod technique to determine validity of tests
Donald Campbell and Donald Fiske
Concurrent validity
statistically significant
Null hypothesis