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GRE Psychology: Measurement And Methodology

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






2. Numerically calculating and expressing correlation - r range -1 to +1 - 0 = no relationship






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






4. Measure mastery in a particular area (e.g. final exam)






5. Might show how often different variables appear; nominal - ordinal - interval - ratio (real zero)






6. Measure the extent to which test measures what it intends to; concurrent - construct - content - face






7. The degree to which an independent variable can predict a dependent variable






8. Fluid intelligence declines with old age while crystallized intelligence does not






9. The hypothesis that no real differences or pattern exist






10. Rosenthal effect; researchers see what they want to see; minimized in double-blind






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






12. Birth order vs. intelligence; the older - the more intelligent; the more children - the less intelligent; the greater spacing - the more intelligent






13. Knowing a fact






14. Like a histogram except that the vertical bars do not touch - various columns are separated by space






15. Step beyond correlations; allows not only identification of relationship between 2 variables - also make predictions






16. Neither purely descriptive nor purely inferential - can only show relationship - not causality - positive and negative correlation






17. Whether test really taps abstract concept being measured






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






19. Tests the same person at multiple time points and looks at changes within that person






20. Overall range or spread - most basic measure of variability - subtracts the lowest value from the highest value in a data set






21. How well a test measures a construct; multitrait-multimethod technique determines validity; internal - external: concurrent - construct - content - face






22. Created multitrait-multimethod technique to determine validity of tests






23. Compares 2 groups of people at the same time point






24. Combines longitudinal and cross-sectional approach






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






27. There is a general factor in intelligence 'g'






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






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






30. Give descriptive names - No order or relationship among the variables other than to separate them into groups - ex: male-female






31. When subjects that drop out are different than those that remain; no longer random






32. For ranks; determining the line that describes a linear relationship






33. How much variation there is among n number of scores in a distribution






34. Different subjects of different ages are compared - faster - easier






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 -






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






37. The process of representing or analyzing numerical data






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






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






40. Analyses how a large group responded to each item on the measure; weeds out problematic questions with low discriminatory value; increases internal consistency






41. Population --> sample/subgroup --> representative and unbiased --> achieved through random sampling --> if it'S not feasible - use convenience sampling instead or stratified sampling






42. Revised Binet'S version - used with children - organized by age level - Best known predictor of future academic achievement






43. For children 6-16






44. Number of SD a score is from the mean - For normal distribution - (-3 to +3)






45. Draw a person of each sex and tell a story about them






46. How a researcher attempts to examine a hypothesis - different questions call for different approaches - some approaches are more scientific than others






47. Capable of showing order and pacing because equal spaces lie between the values - do not include real zero - ex: temperature






48. Bell curve; larger the sample - greater chance of having a normal distribution






49. Studying the same objects at different points in the lifespan and provides better - more valid results than most other methods - costly - time commitment






50. Not IQ - It is unlikely IQ captures all facets of it