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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. Whether content covers a good sample of construct being measured
Content validity
placebo effect
Thematic Apperception Test (TAT)
Selective attrition
2. Numerically calculating and expressing correlation - r range -1 to +1 - 0 = no relationship
Pearson r correlation coefficient
Internal validity
Reactance
One-way ANOVA
3. 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
variance and standard deviation
One-way ANOVA
Content validity
Illusory correlation
4. Measure mastery in a particular area (e.g. final exam)
double-blind experiment
Criterion-referenced tests
Selective attrition
Population & related
5. Might show how often different variables appear; nominal - ordinal - interval - ratio (real zero)
Demand characteristic
Reliability (+types)
cohort effect
Frequency distributions (+variables)
6. Measure the extent to which test measures what it intends to; concurrent - construct - content - face
Spearman r correlation coefficient
Thematic Apperception Test (TAT)
Crystallized intelligence
External validity (+types)
7. The degree to which an independent variable can predict a dependent variable
Construct validity
Draw-A-Person Test
predictive value
Lie detector tests
8. Fluid intelligence declines with old age while crystallized intelligence does not
John Horn and Raymond Cattell
Statistical regression
Linear regression
IQ Binet'S equation
9. The hypothesis that no real differences or pattern exist
Item analysis (reliability)
Aptitude tests
Reliability (+types)
Null hypothesis
10. Rosenthal effect; researchers see what they want to see; minimized in double-blind
Validity (+types)
Rotter Incomplete Sentence Blank
Charles Spearmen
Experimenter bias
11. 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
Thematic Apperception Test (TAT)
Meta-analysis
statistics
One-way ANOVA
12. Birth order vs. intelligence; the older - the more intelligent; the more children - the less intelligent; the greater spacing - the more intelligent
cohort effect
Robert Zajonc
bar graph
Percentages under normal distribution based on SDs (from mean to end)
13. Knowing a fact
Crystallized intelligence
Beck Depression Inventory (BDI)
Item analysis (reliability)
Robert Zajonc
14. Like a histogram except that the vertical bars do not touch - various columns are separated by space
bar graph
mental age
Null hypothesis
Wechsler Adult Intelligence Scale (WAIS)
15. Step beyond correlations; allows not only identification of relationship between 2 variables - also make predictions
Statistical regression
Test-retest reliability
Draw-A-Person Test
External validity (+types)
16. Neither purely descriptive nor purely inferential - can only show relationship - not causality - positive and negative correlation
Correlational relationships
California Personality Inventory (CPI)
Continuous data
ANOVA/analysis of variance
17. Whether test really taps abstract concept being measured
Z-scores
Construct validity
Robert Zajonc
Split-half reliability
18. 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)
Internal validity
Wechsler Adult Intelligence Scale (WAIS)
Crystallized intelligence
19. Tests the same person at multiple time points and looks at changes within that person
within subject
Domain-referenced tests
One-way ANOVA
Rotter Incomplete Sentence Blank
20. Overall range or spread - most basic measure of variability - subtracts the lowest value from the highest value in a data set
Domain-referenced tests
standard deviation (calculation)
dependent variable
range
21. How well a test measures a construct; multitrait-multimethod technique determines validity; internal - external: concurrent - construct - content - face
Z-scores
Validity (+types)
Hawthorne effect
Intelligence
22. Created multitrait-multimethod technique to determine validity of tests
cross-sectional design
Donald Campbell and Donald Fiske
Validity (+types)
median
23. Compares 2 groups of people at the same time point
range
predictive value
between subject
double-blind experiment
24. Combines longitudinal and cross-sectional approach
interval variables
Internal-External Locus of Control Scale
cohort-sequential design
Percentages under normal distribution based on SDs (from mean to end)
25. (Mental age/chronological age)/100 - Highest age = 16
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26. 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
Reactance
Robert Zajonc
Linear regression
Factorial analysis of variance
27. There is a general factor in intelligence 'g'
Aptitude tests
Charles Spearmen
Construct validity
Myers-Brigg Type Indicator (MBTI)
28. Attitude change in response to feeling that options are limited; e.g. dislike experiment and intentionally behaving unnaturally - or being set on a certain flavour of ice cream as soon as told it is sold out
Reactance
Rotter Incomplete Sentence Blank
Linear regression
cohort-sequential design
29. 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
research design
Lie detector tests
Myers-Brigg Type Indicator (MBTI)
Factorial analysis of variance
30. Give descriptive names - No order or relationship among the variables other than to separate them into groups - ex: male-female
Internal validity
Goodenough Draw-A-Man Test
Thematic Apperception Test (TAT)
nominal variables
31. When subjects that drop out are different than those that remain; no longer random
Crystallized intelligence
Rosenzweig Picture-Frustration (P-F) Study
Linear regression
Selective attrition
32. For ranks; determining the line that describes a linear relationship
ordinal variables
T-test
John Horn and Raymond Cattell
Spearman r correlation coefficient
33. How much variation there is among n number of scores in a distribution
Goodenough Draw-A-Man Test
variance and standard deviation
Hawthorne effect
Fluid intelligence
34. Different subjects of different ages are compared - faster - easier
F-scale or F-ratio
standard error of mean
cross-sectional design
placebo effect
35. 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 -
Factorial analysis of variance
statistics
Chi-square test
mode
36. 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
placebo
Reactance
Discrete data
generalizability
37. The process of representing or analyzing numerical data
Charles Spearmen
statistics
Hawthorne effect
Statistical regression
38. 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
percentiles
Population & related
Rosenthal effect
Curvilinear relationship
39. 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
One-way ANOVA
independent variable
Empirical-keying or criterion-keying approach
Frequency distributions (+variables)
40. Analyses how a large group responded to each item on the measure; weeds out problematic questions with low discriminatory value; increases internal consistency
External validity (+types)
Rotter Incomplete Sentence Blank
IQ Binet'S equation
Item analysis (reliability)
41. Population --> sample/subgroup --> representative and unbiased --> achieved through random sampling --> if it'S not feasible - use convenience sampling instead or stratified sampling
statistics
Population & related
random sampling
Anne Anastasi
42. Revised Binet'S version - used with children - organized by age level - Best known predictor of future academic achievement
Robert Zajonc
histogram
Stanford-Binet Intelligence Scale
Demand characteristic
43. For children 6-16
Wechsler Intelligence Scale for Children (WISC-R)
Chi-square test
Rosenthal effect
T-test
44. Number of SD a score is from the mean - For normal distribution - (-3 to +3)
Z-scores
Inferential statistics
Type I and II errors
External validity (+types)
45. Draw a person of each sex and tell a story about them
Walter Mischel
Draw-A-Person Test
ratio variables
John Horn and Raymond Cattell
46. How a researcher attempts to examine a hypothesis - different questions call for different approaches - some approaches are more scientific than others
research design
Experimenter bias
Crystallized intelligence
Experimental design
47. Capable of showing order and pacing because equal spaces lie between the values - do not include real zero - ex: temperature
Q-sort/measure
research design
social desirability
interval variables
48. Bell curve; larger the sample - greater chance of having a normal distribution
Beck Depression Inventory (BDI)
Type I and II errors
John Horn and Raymond Cattell
normal distribution(+characteristic)
49. Studying the same objects at different points in the lifespan and provides better - more valid results than most other methods - costly - time commitment
bar graph
Standard normal distributions
standard error of mean
Longitudinal design
50. Not IQ - It is unlikely IQ captures all facets of it
Wechsler Preschool and Primary Scale of Intelligence (WPPSI)
Intelligence
Z-scores
ANOVA/analysis of variance