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. Notable for cross-cultural application and simple directions - to make the best picture of a man - scored based on detail and accuracy - not artistic talent
cohort-sequential design
Goodenough Draw-A-Man Test
One-way ANOVA
Intelligence
2. How much variation there is among n number of scores in a distribution
T-score
variance and standard deviation
statistically significant
nominal variables
3. Give descriptive names - No order or relationship among the variables other than to separate them into groups - ex: male-female
California Personality Inventory (CPI)
nominal variables
Reactance
F-scale or F-ratio
4. Not to diagnose depression but assess severity of depressive symptoms; used by researcher or clinician to track course of depressive symptoms
Wechsler Adult Intelligence Scale (WAIS)
Longitudinal design
Beck Depression Inventory (BDI)
placebo
5. Studying the same objects at different points in the lifespan and provides better - more valid results than most other methods - costly - time commitment
Curvilinear relationship
Longitudinal design
statistics
Reactance
6. 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
Discrete data
research design
Myers-Brigg Type Indicator (MBTI)
Empirical-keying or criterion-keying approach
7. How well a test measures a construct; multitrait-multimethod technique determines validity; internal - external: concurrent - construct - content - face
Reactance
Validity (+types)
Central Tendency (types and distribution differences)
percentiles
8. Does not control - but examines how independent variable affects it
Experimental design
dependent variable
quasi-experimental design
Null hypothesis
9. 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
Central Tendency (types and distribution differences)
F-scale or F-ratio
Q-sort/measure
Minnesota Multiphasic Personality Inventory (MMPI)
10. 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
Nonequivalent control group
Wechsler Intelligence Scale for Children (WISC-R)
Anne Anastasi
11. Internal-External Locus of Control Scale
placebo effect
Julian Rotter
Internal validity
bar graph
12. Transformation of a z-score - mean is 50 and the SD is 10 - T=10(Z)+50
T-score
Draw-A-Person Test
Objective tests (+types)
Bayley Scales of Infant Development
13. The most frequently occurring value
mode
Thematic Apperception Test (TAT)
Wechsler Intelligence Scale for Children (WISC-R)
Concurrent validity
14. When subjects act in ways they think experimenter wants or expects
Wechsler Preschool and Primary Scale of Intelligence (WPPSI)
Demand characteristic
Draw-A-Person Test
dependent variable
15. Used most commonly on standardized test
Content validity
range
percentiles
median
16. Used when equivalent one cannot be isolated
standard error of mean
California Personality Inventory (CPI)
Nonequivalent control group
Wechsler Intelligence Scale for Children (WISC-R)
17. Numerically calculating and expressing correlation - r range -1 to +1 - 0 = no relationship
range
Lie detector tests
Pearson r correlation coefficient
variance (calculation)
18. How a researcher attempts to examine a hypothesis - different questions call for different approaches - some approaches are more scientific than others
research design
ordinal variables
variance and standard deviation
Rotter Incomplete Sentence Blank
19. Naturalistic setting - less control over environment than in lab; generates more hypotheses than able to prove
Projective tests (+types)
Field study
independent variable
standard deviation (calculation)
20. 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
Robert Zajonc
Objective tests (+types)
Content validity
Concurrent validity
21. Every member of the population has an equal chance of being chosen for the sample
Stanford-Binet Intelligence Scale
Objective tests (+types)
random sampling
cohort effect
22. Whether test really taps abstract concept being measured
Construct validity
placebo effect
Rosenzweig Picture-Frustration (P-F) Study
Longitudinal design
23. (Mental age/chronological age)/100 - Highest age = 16
Warning
: Invalid argument supplied for foreach() in
/var/www/html/basicversity.com/show_quiz.php
on line
183
24. Measure how well you know a subject - measure past learning
Achievement tests
random sampling
Crystallized intelligence
Analysis of covariance (ANCOVA)
25. When relationship inferred when there is none - ex: many people think there is a relationship between physical and personality characteristics - when evidence show there is none
Population & related
Illusory correlation
Analysis of covariance (ANCOVA)
confounding variable
26. Birth order vs. intelligence; the older - the more intelligent; the more children - the less intelligent; the greater spacing - the more intelligent
cohort effect
Rosenthal effect
Robert Zajonc
mode
27. Neither the subject nor the experimenter know whether the subject is assigned to the treatment or the control group
double-blind experiment
Meta-analysis
Lewis Terman
cross-sectional design
28. 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%
Lie detector tests
generalizability
Alpha levels
mode
29. Overall range or spread - most basic measure of variability - subtracts the lowest value from the highest value in a data set
Fluid intelligence
range
T-test
Stanford-Binet Intelligence Scale
30. Created to determine whether a person feels responsible for things that happen (internal) or no control over events in life (external)
Internal-External Locus of Control Scale
External validity (+types)
Experimenter bias
Longitudinal design
31. For even number of values in the set - take the average of the two middle value
Walter Mischel
John Horn and Raymond Cattell
Curvilinear relationship
median
32. Tests whether at least 2 groups co-vary - can adjust for preexisting differences between groups
Analysis of covariance (ANCOVA)
Hawthorne effect
Wechsler Adult Intelligence Scale (WAIS)
independent variable
33. Step beyond correlations; allows not only identification of relationship between 2 variables - also make predictions
Curvilinear relationship
Statistical regression
Graphs (types)
independent variable
34. Originally used with free association techniques; word called out - subject says next word in mind
Word Association Test
ANOVA/analysis of variance
Minnesota Multiphasic Personality Inventory (MMPI)
between subject
35. Subjects alter behaviour because they are being observed
Hawthorne effect
Learn the shape of different distributions
F-scale or F-ratio
Julian Rotter
36. Different subjects of different ages are compared - faster - easier
Donald Campbell and Donald Fiske
cross-sectional design
Variability
Inferential statistics
37. Combines longitudinal and cross-sectional approach
social desirability
Walter Mischel
cohort-sequential design
statistics
38. Aims to match demographic characteristics to population (i.e. 50% female - etc)
Two-way ANOVA
stratified sampling
Crystallized intelligence
cross-sectional design
39. Fluid intelligence declines with old age while crystallized intelligence does not
John Horn and Raymond Cattell
Alfred Binet
ordinal variables
Bayley Scales of Infant Development
40. Similar to word association - finish incomplete sentences
mode
Two-way ANOVA
Wechsler Preschool and Primary Scale of Intelligence (WPPSI)
Rotter Incomplete Sentence Blank
41. Measures the extent to which items in a measure 'hang together' and test the same thing
Z-scores
Internal validity
Wechsler Intelligence Scale for Children (WISC-R)
Julian Rotter
42. Whether test items look like they measure the construct
Face validity
California Personality Inventory (CPI)
Stanford-Binet Intelligence Scale
Longitudinal design
43. Normal curve - negatively skewed distribution - positively sknewed distribution - bimodal distribution - platykuric distribution
confounding variable
normal distribution(+characteristic)
Learn the shape of different distributions
Two-way ANOVA
44. There is a general factor in intelligence 'g'
ANOVA/analysis of variance
Charles Spearmen
Q-sort/measure
Construct validity
45. Mean is 0 - and SD=1 - This with Z-score allow you to compare one person'S score on two different distributions
Standard normal distributions
interval variables
Z-scores
Hawthorne effect
46. The degree to which an independent variable can predict a dependent variable
Stanford-Binet Intelligence Scale
Domain-referenced tests
predictive value
Strong-Campbell Interest Inventory
47. Assess extent interests and strengths match those found by professionals in a particular job field
statistics
Vocational tests
Descriptive statistics (+types)
Field study
48. Capable of showing order and pacing because equal spaces lie between the values - do not include real zero - ex: temperature
Crystallized intelligence
John Horn and Raymond Cattell
Population & related
interval variables
49. 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
Learn the shape of different distributions
Concurrent validity
Acquiescence
variance (calculation)
50. Experimenter bias; researchers see what they want to see; minimized in double-blind
research design
Wechsler Intelligence Scale for Children (WISC-R)
Rosenthal effect
Inferential statistics