PSYCH 501 Module 4

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ralissa
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187347
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PSYCH 501 Module 4
Updated:
2012-12-12 11:32:17
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Definitions for module 4
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  1. predictor variable
    a variable which is believed to predict another variable
  2. covariance
    describes the linear association between two quantitative variables
  3. scatterplot
    graphical representation of the association between two quantitative variables
  4. Pearson Correlation
    • a measure of the association between two variables which is defined on a scale from -1 to 1, with 1 being a perfect positive relationship and a -1 being a perfect negative relationship
    • ¬†
  5. coefficient of determination
    measure of the association between two variables, equal to the squared Pearson correlation. Describes the proportion of variance in one variable that is linearly associated with the other variable
  6. linear regression model
    can be used to descrive the relation between x and y in a random sample of participants
  7. random-x model
    linear regression model in which each person in a random sample is assigned a pair of x and y scores, where the x values observed in the sample will not be known in advance.
  8. fixed-x model
    linear regression model in which the values of x are predetermined by the researcher
  9. slope
    describes the change in the predicted y score associated with any 1-point increase in x; 1
  10. least squares estimate
    the unique values that minimize the sum of all squared residual scores ()
  11. centering predictor variable
    subtracting  from each x score so that the predictor variable's mean will equal 0 and
  12. Fisher transformation
    • used to transform a Pearson correlation coefficient to obtain a confidence interval
  13. dummy coded predictor variable
    setting xi=1 for every participant in the first group and xi=0 for every participant in the second group; in this model,
  14. point-biserial correlation
    describes the strength of the relation between a quantitative response variable and a dichotomous predictor variable
  15. reliability
    the squared Pearson correlation between the true scorfes and the measured scores
  16. measurement error
    the difference between the true score and the observed measurement of the true score
  17. alternative form reliability
    the Pearson correlation between two measurements of a randomly selected participant's particular attribute
  18. test-retest relibaility
    Pearson correlation between two occasions of the same form for a randomly selected participant
  19. inter-rater reliability
    the Pearson correlation between two measurements of a randomly selected participant given by two different raters
  20. validity
    the degree to which a measurement assesses the attribute it claims to measure
  21. criterion validity
    obtained by assessing the magnitude of a correlation (Pearson or point-biserial) between the measurement in question and some objective behavioral criterion or performance on a specific task
  22. construct validity
    obtained by assessing the magnitude of a correlation between the measurement in question (y) and the measurements of several other psychological measurements
  23. linearity assumption
    the assumption that the relation between y and x is linear
  24. errror normality assumption
    the assumption that the prediction errors have an approximate normal distribution in the study population
  25. bivariate normality assumption
    in random-x models, the assumption that x and y have an approximate bivariate normaldistribution
  26. outlier
    unusually small or large x or y scores
  27. data transformations
    A logarithmic, square root, or reciprocal transformation of an x or y score to normalize the scores

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