collier last test

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  1. qualitative data
    • categorical or classification data
    • ex. gender, race, where you live, political affiliation
    • much test data are qualitative
    • ex. responses to a given test item can be right or wrong or a,b,c, or d
  2. quantitative data
    test scores, reaction time, heart rate, brain-wave measurements
  3. lures/distractors
    wrong answers on a multiple choice test
  4. item analysis
    if a test has only two answers (the right and wrong answer) then indicating which answer was selected is basically the same as indicating whether the correct answer was chosen
  5. Two kinds of test theory
    • classical test theory (older)
    • IRT (item response theory) newer replacing classical test theory
  6. item discrimination
    • the ability of the item to tell the difference between different people
    • an item that everyone got right does not discriminate
    • an item that everyone got wrong does not discriminate
    • items that are too easy or too difficult have low discriminations
  7. item-test/item whole correlation
    the correltation between a particular item and the scores on the entire test
  8. what does it mean when the test-item correlation is high
    • it means that ppl who got the item right tend to have high test scores, and ppl who got it wrong tend to have low test scores.
    • the item discriminates between ppl who knew the material and ppl who didnt
    • the test item correlation is used as an index of item discrimination
  9. average test item correlation
    • tells how much they all tend to intercorrelate.
    • can also be called measure of test coherence
  10. measure of test coherence
    whetherthe items all test the same thing
  11. average intercorrelation
    called Cronbach's Alpha and is the most standard measure of test reliability
  12. Kuder-Richardson 
    the version of this formula that applies totests where there are right and wrong answers
  13. difficulty
    the percent correct for an item
  14. reliability
    the item-whole score correlation
  15. process of test development
    • 1. make up a bunch of test items and create a test
    • 2. give the test to alot of ppl
    • 3. get the correlations among the items
    • 4. throw out items that correlatepoorly with the reamining items
    • 5. if there are too few items left, creae sme new ones and start over
    • 6. continue this until the test has enough items tha all have high correlations w/ each other
  16. multivariate research
    • gathering many variables
    • testing and survey research
  17. multivariate statistical analysis
    taking complex data and reducing it to simpler forms
  18. qualitative (multivariate methods)
    • categorical or classification data
    • ex. gender, race, poltical affiliation
  19. quantitative (mulivariate methods)
    test scores, reaction time, heart rate, brain-wave measurements
  20. factor analysis
    • a method for construct validation
    • gives us a method to Xray inside the vlack box of abstract construct that we are interested in
  21. properties of a correlation matrix
    • it contains the correlations or every item with every other item
    • it is square
    • the diagonal elements represent the correlation of each item with itsel, and so these are always 1
    • it is symmetrical
  22. simplifying the correlation matrix
    • technique for packaging together variables into super variables
    • do this by looking for items that correlate highly with each other, and packaging them together
    • if looking at one trait all items should intercorrelate, and should get one super variable that can be name after the trait
  23. True/False:
    Factor analysis and PCA are similar techniques
  24. factors
    both factor analysis and principal components analysis boil down the correlation matrix to a smaller number of super variables
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collier last test
2012-11-20 02:17:51
collier last test

collier last test
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